#ai face detection camera USA

[zoyeleanor]

The Role of Embedded Cameras in Revolutionizing Remote Diagnostics for Telemedicine

Embedded cameras are starting to become a game-changer in the rapidly developing field of telemedicine. These small, powerful devices are leading the way in changing how doctors diagnose and treat patients remotely as healthcare becomes more digital.

What Are Embedded Cameras?

Embedded cameras are compact, high-performance imaging devices integrated into various electronic systems. Unlike standalone cameras, these devices are seamlessly embedded into medical equipment, computers, or mobile devices, providing high-quality video and image capture without the need for separate hardware.

Enhancing Remote Diagnostics

One of the primary ways embedded cameras are revolutionizing telemedicine is through enhanced remote diagnostics. Traditionally, remote consultations relied on verbal descriptions and basic video calls, which often led to incomplete assessments. With embedded cameras, healthcare providers can now conduct detailed visual examinations from afar.

These cameras offer high-resolution imaging, allowing doctors to observe fine details that are crucial for accurate diagnoses. Whether it’s monitoring a patient’s skin condition, examining wounds, or assessing physical symptoms, the clarity provided by embedded cameras ensures that remote consultations are as effective as in-person visits.

Real-Time Patient Monitoring

Embedded cameras are also pivotal in real-time patient monitoring. In telemedicine, continuous observation of patients’ health conditions is often necessary, especially for those with chronic illnesses or undergoing rehabilitation. Cameras embedded in home health devices can transmit live footage to healthcare providers, enabling timely interventions and adjustments to treatment plans.

For example, a patient recovering from surgery might use an embedded camera in their home monitoring system to provide their doctor with real-time views of their healing progress. This allows the doctor to make informed decisions about the patient’s care without requiring frequent office visits.

Integration with AI and Machine Learning

The integration of embedded cameras with artificial intelligence (AI) and machine learning is further enhancing remote diagnostics. Advanced algorithms can analyze video feeds from embedded cameras to detect patterns and anomalies that might be missed by the human eye. This synergy between technology and healthcare is leading to earlier detection of conditions and more personalized treatment plans.

Improving Accessibility and Convenience

In the USA, where access to healthcare can vary greatly depending on location, embedded cameras play a crucial role in bridging the gap. Rural and underserved communities often face challenges in accessing specialized medical care. Embedded cameras enable these communities to connect with top-tier specialists remotely, making healthcare more accessible and convenient.

Additionally, the convenience of remote diagnostics reduces the need for travel, which can be a significant barrier for many patients. Embedded cameras allow individuals to receive high-quality medical care from the comfort of their own homes, saving time and reducing stress.

A Future of Enhanced Care

As telemedicine continues to grow, the role of embedded cameras will only become more significant. Their ability to provide detailed, real-time visual information is transforming remote diagnostics and paving the way for a new era of healthcare.

With ongoing advancements in technology, the integration of embedded cameras will likely become even more sophisticated, further improving the accuracy and efficiency of remote medical care. For patients and healthcare providers alike, this means a future where high-quality, accessible medical consultations are just a click away.

The impact of embedded cameras on telemedicine is profound, offering new possibilities for remote care and making high-quality healthcare accessible to more people across the USA.

[spookysaladchaos]

Driver and Cabin Monitoring System, Global Market Size Forecast, Top 10 Players Rank and Market Share

Driver and Cabin Monitoring Market Summary

According to the new market research report “Global Driver and Cabin Monitoring System Market Report 2023-2029”, published by QYResearch, the global Driver and Cabin Monitoring System market size is projected to reach USD 2056.4 million by 2029, at a CAGR of 23.5% during the forecast period.

Figure.   Global Driver and Cabin Monitoring Market Size (US$ Million), 2018-2029

Based on or includes research from QYResearch: Global Driver and Cabin Monitoring Market Report 2023-2029.

Market Drivers:

Every year more than 1.35 million people are killed in road accidents, and 90 % of these result from human error, often drowsiness or distraction. Automotive interior monitoring system that mitigates the human factor is going to be critical in reducing road traffic deaths.​

A political consensus is growing. All new cars in the EU will require a camera-based DMS by the year 2026, meaning manufacturers need to begin incorporating DMS into their systems now.

Due to the rapid development of autonomous driving in automobiles, Automotive interior monitoring systems have achieved rapid growth and growth driven by the development of AI algorithms, chips, visual technology, and other industries.

Restraint:

The biggest technical challenge of camera-based interior monitoring system is the unclear image recognition under strong or weak light conditions. Also, visual algorithm faces many technical challenges, and many complex situations pose significant challenges to the algorithm.

Currently, in the automotive industry, in-vehicle computing platforms face the challenge of insufficient computing power. Because most of the existing mainstream in-car computing platforms mainly use low-end ARM CPUs/GPUs and lack deep learning chips, there are still difficulties in running algorithms such as face detection, key point detection, face recognition, line of sight tracking, gesture recognition, etc.

Regarding aftermarket, there are no comprehensive industry standards and insufficient regulation, and low industry entry barriers make some suppliers engaging in vicious competition at low prices.

Opportunity:

Considering the mass implementation of automated driving systems and the need for improving driving safety, automotive interior monitoring system has a bright future in the automotive market. And automotive interior monitoring system will proliferate into passenger vehicles at a substantial rate in the coming years.

Figure.   Global Driver and Cabin Monitoring Top 10 Players Ranking and Market Share（Continually updated）

Based on or includes research from QYResearch: Global Driver and Cabin Monitoring Market Report 2023-2029.

This report profiles key players of Driver and Cabin Monitoring such as Continental, Visteon Corporation, and Valeo.

In 2022, the global top five Driver and Cabin Monitoring players account for 44.3% of market share in terms of revenue. Above figure shows the key players ranked by revenue in Driver and Cabin Monitoring.

Figure.   Driver and Cabin Monitoring, Global Market Size, Split by Product Segment

Based on or includes research from QYResearch: Global Driver and Cabin Monitoring Market Report 2023-2029.

In terms of product type, Camera-based is the largest segment, hold a share of 93.6% in 2022.

Figure.   Driver and Cabin Monitoring, Global Market Size, Split by Application Segment

Based on or includes research from QYResearch: Global Driver and Cabin Monitoring Market Report 2023-2029.

In terms of product application, Passenger Cars are the largest application, hold a share of 63.9% in 2022.

Figure.   Driver and Cabin Monitoring, Global Market Size, Split by Region

Based on or includes research from QYResearch: Global Driver and Cabin Monitoring Market Report 2023-2029.

About QYResearch

QYResearch founded in California, USA in 2007.It is a leading global market research and consulting company. With over 16 years’ experience and professional research team in various cities over the world QY Research focuses on management consulting, database and seminar services, IPO consulting, industry chain research and customized research to help our clients in providing non-linear revenue model and make them successful. We are globally recognized for our expansive portfolio of services, good corporate citizenship, and our strong commitment to sustainability. Up to now, we have cooperated with more than 60,000 clients across five continents. Let’s work closely with you and build a bold and better future.

QYResearch is a world-renowned large-scale consulting company. The industry covers various high-tech industry chain market segments, spanning the semiconductor industry chain (semiconductor equipment and parts, semiconductor materials, ICs, Foundry, packaging and testing, discrete devices, sensors, optoelectronic devices), photovoltaic industry chain (equipment, cells, modules, auxiliary material brackets, inverters, power station terminals), new energy automobile industry chain (batteries and materials, auto parts, batteries, motors, electronic control, automotive semiconductors, etc.), communication industry chain (communication system equipment, terminal equipment, electronic components, RF front-end, optical modules, 4G/5G/6G, broadband, IoT, digital economy, AI), advanced materials industry Chain (metal materials, polymer materials, ceramic materials, nano materials, etc.), machinery manufacturing industry chain (CNC machine tools, construction machinery, electrical machinery, 3C automation, industrial robots, lasers, industrial control, drones), food, beverages and pharmaceuticals, medical equipment, agriculture, etc.

[appsstoreai]

Understanding CanOSH and CCOHS- Canada’s OSHA Standard

Few of our previous posts have already discussed occupational safety and health administration (OSHA) for three major countries; USA, UK, and Canada. OSHA compliance for these three countries has been almost similar. Talking about Canada- the next major country, their employee safety, and health administration policy is different than OSHA’s. If you talk to people in Canada, employees there are familiar with CanOSH and CCOHS. With these two standards, the Canadian government ensures that workers are safe across various organizations and industrial companies running across the country.

What is CanOSH?

CanOSH is an occupational safety and health resource that explains rights related to employee and their safety for Canadian citizens. With the name CanOSH, people might think that it’s a Canadian form of OSHA. But, unlike CanOSH does act as a regulator. Instead, it’s a resource provider for citizens.

What’s the purpose of CanOSH?

The main purpose of CCOSH and CanOSH is to provide a legal form of informational framework to protect the rights of employees working nationwide. Let’s understand how it ensures compliance:

Formulating duties for all Canada’s entire workplace to encourage organizations to establish a safe and robust internal working environment.

Establishing policies and procedures to tackle workplace hazards.

Enforcing laws for organizations that are not serious about employee safety.

Understanding CanOSH and CCOHS

CCOSH and CanOSH are said to be equivalent to Organizational Safety and Health Administration act. *-However, as mentioned, it’s a resource collection that provides safety rules and regulations for organizations. So, what’s the difference between CanOSH and CCOHS when both of them are resource enablers? The difference is that CCOHS provides a resource for employers. Whereas, CanOSH provides resources for employees and the rest of the citizens.

Employer responsibility in CCOHS:

Workers in the CCOHS have a moral responsibility to report a hazard or a violation of Canadian OSHA at the workplace to keep the workplace risk-free and healthy.

Employee responsibility in CanOSH

Employers, supervisors, and engineers must address the hazards and acquaint the workplace with complete information on CanOSH rules violations.

Employers should respect the workers and help them show respect for workplace security and safety compliance.

Maintain a strong internal responsibility system for a 100% safe workplace.

How computer vision apps can be used for CanOSH and CCOHS compliance?

Artificial intelligence has an integral role in ensuring safety and compliance in organizations, including industrial workplaces. From monitoring personal protective equipment to tracking machine usage, AI-enabled apps such as computer vision apps help organizations to comply with CanOSH and CCOHS rules across organizations. With computer vision apps, organizations can monitor the following compliance:

PPE clothing & apparel A computer vision app tracks and detects if workers are wearing PPE apparel and other clothing as per CCOHS compliance.

Face mask detection Detects if employees wear masks properly at the workplace. A computer vision app further discovers the quality of masks as per CCOHS rules.

Smart camera tracking With computer vision apps, organizations make their camera feed 2X smarter so that it can track employees and their activities during work hours.

Safety Footwear Tracks employees and ensure they are wearing safety footwear while working at the site.

Eye protection Ensures workers are wearing eye-protecting glasses to reduce the risk of any kind of eye injury.

Safety gloves Monitors employees and informs the admin about employees not wearing safety gloves.

Helmet protection Helmet protection app monitors employees to ensure they are wearing helmets properly as per CCOHS compliance.

Hearing protection The smart camera analyzes the workplace environment and ensures that the sound level doesn’t exceed the suggested level.

Accident monitoring Computer vision apps monitor various processes and identify potential hazards for an accident-free workplace.

Penalties for not complying with Canadian CCOHS

The following are the penalties for not complying with CCOHS regulations:

A financial fine of up to $50,000 for individuals and imprisonment of up to 12 months.

A financial fine of up to $1500,000 for the organization’s directors and upper administrations.

A financial fine of up to $1,500,000 for corporations.

End line As to conclude, organizations do not have any alternative to compliance with CanOSH and CCOHS standards. For 100% compliance, companies should leverage AI and artificial intelligence technologies into computer vision applications. This only requires seamless integration of your existing camera with computer vision apps. Get complete information by connecting with the experts at AppsStore.ai.

[ceyhanmedya]

Autonomous Car

New Post has been published on https://bankakredin.com/what-is-an-autonomous-car-how-does-an-autonomous-vehicle-work/

Autonomous Car

What is an Autonomous Car? How Does an Autonomous Vehicle Work?

Autonomous driving is a broad concept that includes a set of driving assistants, also called ADAS (Advanced Driver Assistance Systems in Turkish). This AI- powered assistant has the ability to drive the car without human intervention.

What is an Autonomous Car?

An autonomous car is a vehicle capable of performing all the driving functions between the start and the destination at any time, without the need for human intervention, beyond specifying the start and end point of the journey. All intermediate stages in which a driver’s action is required imply that autonomy is limited, not full.

Currently, there is no official autonomous car on the market, but there are different projects under development.

ADAS: Advanced Driver Assistance Systems

ADAS are  driving assistants found in existing cars to prevent an accident from occurring as much as possible . They need a set of sensors to calculate distances, detect objects and analyze traffic conditions. 

With the information analyzed by these sensors, the vehicle electronics has the ability to take predetermined decisions and affect the accelerator, brake or steering wheel, and also warn the driver in case of detection of risks that require urgent intervention.

Autonomous Driving Levels

To describe the level of interference these systems interfere with a vehicle’s maneuverability,  the Society of Automotive Engineers (SAE) has defined six levels, from 0 to 5. As you can imagine, the highest level requires no human intervention for any driving.

The most advanced cars on the market today have level 2+, and some were able to reach level 3 under very special circumstances. Conventional level 2 has become pretty standard and this driving aid is relatively inexpensive.

Technologies Used in Autonomous Cars

It’s not enough for a car to simply have an array of sensors, radars and cameras to navigate without driver intervention or even passengers; It is also necessary to communicate with the environment: learn the status of other vehicles and road infrastructure, exchange information about possible accidents on the road. Therefore, full autonomy requires an artificial intelligence-equipped environment with the so-called ” internet of things ” IoT.

Some cars on the market have very limited ” self-driving ” capabilities. In fact, these are remote parking functions, where the driver steers the car from an external device (key or mobile phone).

Brands Developing Autonomous Cars

The autonomous car is being cited as the next battleground after the electric transition. The most important companies developing autonomous vehicles, from giant automobile manufacturers to new companies that attract investment,  are as follows:

Tesla

Pony.ai (developing AI-powered assistant)

Waymo (owned by Google’s parent company)

Apple

Kia-Hyundai

Ford

Audi

VW Group

Mercedes

Huawei

When Will Autonomous Cars Become Real?

Artificial intelligence and the concept of ” driver-connected car ” need to advance for autonomous vehicles to become reality. Learning from the endless situations that can occur in any driving scenario, these devices allow developers to create new response models to unforeseen events. 

If a traffic situation is not foreseen and therefore there is no programmed response, existing autonomous cars require the driver to intervene as they do not have any decision-making capacity in the face of it.

It is estimated that autonomous vehicles will be able to meet the total mobility demand by 2046, once the ongoing regulatory issues in regions such as the EU, USA and UK are resolved  . Based on this outcome, many countries are expected not to interfere with autonomous driving and allow it on public roads.

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[crewartproduction-blog]

Technology Breakthroughs 2019

what is technology:

technology is the knowledge of techniques and processes mixed with skills and methods that enables human to apply this knowledge, technology had started by the pre-historic man when he used a very simple tools to secure his living from food and protection, then technology uses evolved from just a surviving tool to become the backbone of living that interfered in every single detail of human daily life, from the Toothpick to the space-traveling that is like a dream coming true as their rich tourists had made a space trip and its expected that it will be common and affordable trip in the upcoming years, so let’s talk about the most exciting technology breakthroughs in 2019.

Top Breakthroughs

5G Technology:

2019 is going to witness the releasing of the fifth generation of cellular mobile communication (5G) that featured with reduced latency, energy saving, cost reduction, higher system capacity, and massive device connectivity, and it’s the natural evolution of the 4G Technology that had been released on 2009 in Sweden and that was a great breakthrough in the history of mobile internet that the internet speed could reach 100 megabytes per second for high mobility mobile communication, so let’s get back to 5G technology that its speed is expected to reach 2500 MB (Megabyte) per second as peck performance, 5G mobile devices had seen a great improvement in technicality as it depend on a cell communicate by radio waves with a local antenna array and automated transceiver in the cell with low power consumption rate the antenna is connected with the telephone network through optical fiber cables or wireless backhaul connection, the devices that will equip the 5G technology is going to have 4G LTE capability as the 5G access is not available everywhere till now, the 5G is going to be used in the autonomous vehicles to support it with data about the surrounding environment in real time and nearby vehicles that could exchange their locations and intentions, the roadway is also able to deliver traffic conditions immediately ahead, which will ease the task of driving, also 5G technology is going to be compatible for laptops computers to enhance its Internet communication.

Virtual Reality (VR):

Virtual reality (VR) technology had started in the early 1950th as Morton Heling wrote about the “theater experience”, and built a prototype of Sensorama vision dubbed in 1962, this device displays engaged multiple scenes, then he developed the “Telesphere Mask”, the year 1968 had seen the releasing of the first head mounting display (HMD) system for simulation applications by Douglas Engelbart and other scientists, the 70th had seen a great leap in the virtual reality technology by interfering in many fields like medical, military and even space science as David Em was the first one to produce navigable virtual worlds in NASA laboratory, in 1979 Eric Howlett developed the Extra Perspective (LEEP) optical system which make the virtual reality helmets available today, 1991 had seen the invention of the first cubic impressive room allowing people to see their own bodies in relation to each other’s in the room, between the years 1982 and 1992 Nicole Stenger created the first real time interactive impressive movie that viewed by using a dataglove and a high resolution googles, then the new millennium comes with new update in VR technology, by the year 2001 the first pc based on cubic room had been invented, in the year 2007 google had released the street panoramic view by using 3D stereoscopic mode, 2013 had seen the start of using the virtual reality technology in smart phones by using a headset that used in virtual and augmentation of reality, the Oculus VR project had seen the light Valve Corporation, in the year 2014 Facebook had bought the Oculus VR for 2 Million dollar, and also Sony had announced the launch of the PlayStation VR project, In the year 2015 Google had announced the launch of cardboard a do-it-yourself stereoscopic viewer for smartphones, 2016 had seen a great leap in the VR technology development by many companies specially HTC which had shipped the Vive Steam VR headset as the major commercial release in this year, Sony had continued the development of the wireless headset and evolved it and released the Vive for PlayStation VR. 2019 is going to see a great leap in VR technology as Sony is working to release 3D Rubber Motion Controller for PlayStation VR, SOMNIACS company is working on Somniacs Birdly VR Flying Simulator, but this will not be the last update in the VR technology.

Artificial intelligence (AI) technology

Artificial intelligence concept had started to be known from the year 1940 by the invention of the programmable digital computer, the machine based on the abstract essence of mathematical reasoning, Dartmouth college had founded the AI research field in the year 1956, by the year 1973 the artificial inelegance had faced a new challenge from the USA and the British governments as they stopped the funding undirected research into artificial intelligence, the investors started to take the role of the governments in the funding this research but by the 80th they started to withdraw from this business because of the absence of the needed computer power (hardware), but this all had changed by the beginning of the 21 century as that the machine learning was successfully solved a lot of academic and industrial problems, the AI development in the new millennium started with the creation of the interactive toys (smart toys) in the year 2000, in the year 2004 Nasa had navigated the surface of Mars with autonomously robotic exploration rovers, in 2005 Honda released a humanoid robot that is able to walk as fast as humans and he worked as a food servant in restaurant, but the year 2005 had seen a new thinking in the AI technology by the initiation of the blue brain project that aimed to identify the structure of human brain and detect its function in disease and health, between years 2010 and 2014 the humans are being able to communicate and even speak with robots as in 2011 Apple had launched the Siri project and in year 2012 google had launched Google Now, and then the turn comes on Microsoft that released the smartphone apps the uses the natural language to answer the received questions, make recommendations and even perform actions, Artificial Intelligence (AI) Technology is going to see a great leap in 2019 as this year will see the release of:

1- Automated CCTV security cameras:

that featured by:

It could predict potential vulnerabilities, threats and menace.

Tracking missing children.

Tracking theft vehicles.

Quick action.

Identifying criminals and suspected people between the large crowd.

2-general adversarial networks (GANs):

A new concept that will be released in 2019 that will make your AI smarter as an example it could be able to distinguish between the real image or a realistic image that is created by AI technology.

3-Chatbot:

Chatbot that is also known as Smartbot, Talkbot, chatterbot, IM Bot, interactive agent, conventional interface and artificial conversational entity, the Chatbot concept is an artificial intelligence which conducts a conversation via auditory or textual methods, this technology had started in the early 20th century in the year 1960, but in the middle of the century that this technology had turned from simple conversions to powerful promotional tools for media brands and e-commerce businesses, 80% of companies are expected to be using the Chatbot by the year 2020.

3D Printing

3D printing is a number of various computer controlled processes to create a three-dimension object is made by joining and solidifying the material, 3D printing had started to enter the production industry in the early 80th particularly in 1981 when the Japanese scientist Hideo Kodama has invented two methods for fabricating three dimensional plastic models with photo hardening method, the use of 3D printing in production started with functional or aesthetical prototypes then it turned to be additive manufacturing that it can be used in manufacturing a very complex shape or geometry that is pre designed by 3D model or a CAD file, 2019 is going to see a leap in 3D printing specially in the metal 3D printing which depend on digital model that uses layer by layer material build-up approach which gives the metal a full density and high precision, the metal 3D printing technology is going to be used in manufacturing aerospace, oil & gas, automobile and marine applications, 3D printing is going to use new materials and enter the phase of mass production with high technology machines, 3D printing will see new types in 2019 by these types:

Fused Deposition Modelling (FDM): is also known as Fused Filament Fabrication which is the most commonly available and cheapest type of 3D printing.

stereolithographic (SLA): which is known as the world first 3D printing technology as its history returns to the year 1986, stereolithographic printing is Featured by using mirrors but it also had a big disadvantage that it takes too long to trace the cross-section of an object when compared to DLP.

Digital Light Processing (DLP): this type of 3D printing uses a digital light projector to flash one image for each layer at once or images of multiple flashes for larger parts, the output of this type of 3D printing is a digital image composed of square pixels resulting from rectangular blocks called Voxels.

Selective laser sintering (SLS): its creating objects by using Powder Bed Fusion technology and polymer powder, this type of 3D printing is going to be commonly used due to its low price and this type is featured by using a CO2 laser beam in scanning the object surface.

Material Jetting (MJ): this type of 3D printing has the same concept of normal inkjet printers but the difference in this printing type is that it builds multiple layers of ink upon each other until it turns to solid part, Material Jetting featured by offering objects made from multi-material printing and with full-colour.

Drop On Demand (DOD): this type of 3D printing featured by using a pair of ink Jets, one looks like a wax material and the other used for dissolvable support material, DOD printing featured by using a fly-cutter that skims the build area after the creation of each layer to ensure the commencing of this layer, this type of printing is used in casting the lost wax and suitable for other mould making applications.

Sand binder jetting: mainly this type of 3D printing depends on mixing the PMMA powder with binding liquid as an agent to produce parts colors are added to the mixture through another nozzle, binder jetting useful in production of sand cast molds and cores as they are generally made of artificial sand or (silica), this type of 3D printing is featured with its low cost and quite easily integrated into existing manufacturing of foundry process without disruption.

Metal binder jetting: this type of 3D printing is used in the fabrication of metal objects, as the metal powder is bond together using a more poly binding agent, metal binder jetting is featured by producing complex geometries objects beyond conventional manufacturing techniques, this process done on main steps of infiltration process then adding bronze is the object then we go for the sintering process, the output of this printing type had an issue of non-uniform shrinkage that is solved in the design stage.

Direct Metal Laser Sintering (DMLS): this type of 3D printing is like SLS type but the difference in that it is applied on metal objects, laser is used in fusing the metal powder at a point reaching molecular level, DMLS printing process needs a structural support as the output object is Vulnerable to distortion and wrapping due to residual stress.

Electron Beam Melting (EBM): high energy Electron beam is used in the metal fusion; EBM printing is featured with superior building speed upon any other 3D printing types because of its high energy density.

Financial

Blockchain:

Blockchain or blockchain is a growing list of records called blocks using cryptography, blockchains are resistance to modification of the data that was first described in the year 1991 but it was actually created as public transaction ledger of the cryptocurrency (bitcoin) by Satoshi Nakamoto in the year 2008, it is managed by peer to peer network collectivity adhering to a protocol for internal code communication and validating new blocks once recorded, blockchains has many types:

Public blockchains:

Public blockchains have absolutely no access restrictions, its useful as that anyone has a connection to the internet could send transactions as validator, bitcoins and Ethereum are the most known public blockchains Applications.

Private blockchains:

Private blockchains feathered with high privacy as there is no one could join the network until he had been invited by the network administrations, and even the participant and validator access is restricted, this type of blockchains is the most appropriate for companies that are interested in Blockchain technology because of the high control level, its main implement is in accounting and record keeping producer’s business.

Consortium blockchains:

Consortium blockchains are semi-decentralized as its controlling lies between the hands of many companies might control one node in the network and not just a single organization that controls the network.

Blockchains technology will see a great leap in 2019 as these types will rise:

Blockchain will work as a service (BaaS):

BaaS is a cloud-based service that allows customers to build their own Blockchain powered products and it could be including applications, smart contracts, and other Blockchain features without the need to set up or build Blockchain based infrastructure.

Hybrid Blockchain:

Hybrid Blockchain works by providing the best features and functionality of both private and public blockchains, hybrid Blockchain isn’t widely used but it is considered to be the most appropriate for banks.

Federated Blockchain:

Federated Blockchain is the natural evolution of the normal Blockchain, it looks like the private Blockchain but has more customizable outlook, federated blockchains mainly used in financial services.

Ricardian contracts:

Ricardian contracts are the start of the dependence on legal contracts that cryptographically signed and verified, Ricardian contracts provide unique solutions so that they could be understood without mediator or service for both human and computers.

Interoperability between Blockchains:

Interoperability Blockchains aims to improve information across several networks or other Blockchains networks, the cross chain services improve the daily use of Blockchains, 2019 will see an improvement in the interoperability Blockchains technology, the main applications for Interoperability Blockchains are BlockNet, Aion, WanChain, and others.

Stable Coins:

Stable coins are the side product of the cryptocurrencies, that is affected by the market condition and the stability maintained in all time, most of the stable coins are fiat-chained but they are also backed by commodity stable coins, the main applications for stable coins are everyday currency transaction and P2P payments.

Security Tokens:

Security tokens had replaced the ICOs because it is more secure and protects the investor’s rights redefines the whole investment process, by the current year 2019 investors will tend to use security tokens (STO) than (ICO).

Financial Relegation:

Financial relegation is a type of relegation or supervision, which targets financial institutions with certain requirements, guidelines and restrictions that aims to maintain integrity of the financial system, this system could be handled by government or non-government organization, financial relegation had initiated by the Dutch authorities in the early modern period on the year 1610 as short selling which means that the buyer doesn’t own the asset but he borrows it from the seller and returns it back after short time with profit, then the Financial relegation took its development way until it took the form of banks in our days, the 2010 financial crisis had affected the relegation in a positive way as regulators put a fourth substantial number of new strengthened regulations and expanded requirements, 2018 had seen a great focus on legislative agenda towards protecting the consumers and investors and encouraging financial technology innovation, 2019 is going to see big leap in the financial relegation field as Asian investors will continue their 2018 financial vision to make the trajectory of embedding global post-crisis reforms, and make the Asia-pacific outlook the trends navigating guide across the region, in Europe 2019 is expected to be the year of continuity of regulatory terms, As the first half of the year will be finalizing the legislative initiatives to complete the banking Union, strengthen the EMU, and Capital markets Union.

largest technology construction projects in 2019

London Crossrail:

London Crossrail is the world first continues growing underground system that it extends the railway system with 73 miles (117 kilometers) that links between Berkshire and Buckinghamshire this line holds the name of Elizabeth Line that will be divided into two lines, this huge project expected to cost 23 million Pound, London Crossrail had the approval to start to work on it on 2008 and it’s excepted to launch in autumn 2019.

Benban Solar Park:

Benban solar park will be the world largest photovoltaic power station than expected to generate 1650 (MVP), its located in Upper Egypt particularly in Aswan, the Benban solar park is part of Egypt’s Nubian sun project that aims to be part of generating 20% renewable power of total Egyptian needed power, this Egyptian national project is expected to start working by the end of 2019.

[signity-solutions]

Importance of AI Applications in Facial Identification

This blog is originally published at Dzone on October 25, 2021

Artificial Intelligence (AI) is the latest buzzword in the modern world. It renders smart machines all over the world the ability to perform cognitive functions expected from humans. These functions could be the ability to think logically or engage in a casual conversation or even recognize facial patterns for mood detection and identification. Backed by tools like Natural Language Processing, Machine Learning, Deep Learning, etc., Artificial Intelligence is paving the way for machines to think, talk and act like humans.

Facial Identification Technology is one of the front-runner technologies being facilitated through AI applications. It is capable of identifying and verifying the identification of a person using a digital image or a video frame. In general, facial recognition systems work by comparing the selected facial features from an image with the faces available within a database. Such technology has found use in security systems where it enables cameras to grab facial images which can be compared and identified thereafter. It has also recently found uses in commercial and marketing tools.

There are several AI-based techniques used for facial identification. Some face recognition algorithms extract facial landmarks or features from a given subject’s face and compare them for matching features with other images. Others normalize a range of facial images and then compress the facial data. The meaningful data is then saved, and a probe image is compared with the facial data.

xamples of AI Applications in Facial Identification

Today, various organizations are developing face recognition capabilities based on Artificial Intelligence. Facebook has developed a Deep Learning facial recognition system called “DeepFace.” Deep Learning is an AI-based Machine Learning technique concerned with algorithms inspired by the human brain’s neural networks. Deep Learning makes it possible to use brain simulations and make learning algorithms better and easier to use. Facebook makes use of a nine-layered neural network which has 120 million connection weight and is trained on 4 million connection images uploaded by the Facebook users. The system is said to be 97% accurate.

Similarly, Google’s FaceNet is claimed to be a very accurate method for face identification achieving nearly 86% accuracy. It has an image data set with nearly 260 million images from all over the world, and it can give a name to a face and present images that match the face search.

Some models use predictive modeling techniques to incorporate facial data to understand how humans age. The method has been tested by a process named “de-aging,” which involved taking a picture of an old person and running the Deep Learning algorithms backward to create a younger version of the same person. This younger image was then matched with the original image of the person in his younger days and the results were quite accurate. While there were older studies done on age progression work, this one was far more accurate.

Due to the massive amounts of data sets available for research and the Deep Learning algorithms ability to process this data and put it into work, today’s facial identification technology is going places.

Use-Cases for Facial Identification

Facial identification can have extremely relevant use-cases in several industries.

Passport and Visas — It can control fraud detection for passports and visas. Already, the Australian Passport office is using the automatic face-recognition software, reporting 20% more efficiency in detecting fraud.

Banking — It is also useful in financial institutions like banks and their ATMs. China started using this technology in their ATMs. This has ensured a higher level of security for the card user.

Law Enforcement — Law enforcement agencies can deploy facial recognition systems for the identification of criminals. Many countries including the USA are developing their facial recognition database which will aid the criminal investigations making them swifter and more accurate.

Marketing — In 2013, retail giant Tesco rolled out targeted ads based on demographics like the gender and age of the customers at its petrol stations. It used facial recognition to identify these demographics using an AI-based software. Today, many more companies are aiming relevant advertising to its customer’s basis facial identification as they enter the store by changing the display board ads to suit their personal preferences.

AI-powered facial identification can prevent fraud voting, track attendance and many such tasks in an error-free manner which would also be free from human bias. No matter the application and uses, Artificial Intelligence drives the facial recognition systems used across companies. Subsets of Artificial Intelligence such as Machine Learning and Deep Learning are enabling the collation and processing of troves of images which are compared for facial recognition. Without Artificial Intelligence algorithms, facial recognition systems would be far behind in their existence — both in terms of accuracy as well as speed. Artificial Intelligence is at the heart of facial identification.

[digitaltransformationandtech]

How Artificial Intelligence Detects Faces?

You might’ve heard about face recognition and its different applications. A face recognition system can identify people in videos or static images to put it in simple terms. Many fields use the technology for surveillance and tracking people. Some countries are using face recognition systems more widely than others. But while you may hear about it more frequently now, the technology has been in existence for decades.

Face recognition systems have become more powerful with the integration of Artificial Intelligence. These systems match a detected human image(s) with a database of faces. Typically, face recognition systems perform with 99.5% accuracy on public standard data sets.

With advances in Artificial Intelligence, face detection has gradually moved from computer vision techniques to increasingly complex artificial neural networks, deep learning algorithms, and other sophisticated technologies. The use of Artificial Intelligence has improved the technology to a very high level. It’s found many applications in face analysis, face tracking, and law enforcement, security, entertainment, personal safety, and biometrics.

Let’s have a look at how Artificial Intelligence-powered face recognition technology works.

How AI Face Recognition Works

You find it easy to identify the face of a friend, acquaintance, or family member in an image. You do that based on their features such as eyes, mouth, nose, forehead and how these characteristics appear together.

That is also how a face recognition system works. While you see a face and its features, face recognition technology sees data. The data is stored and accessed. The application of the face recognition algorithm varies and depends on use. The basic steps are as follows.

Step 1: Face detection

The camera locates and detects the image of your face either in a crowd or alone. The image may show you looking straight or in profile.

Step 2: Face analysis

The software analyzes the detected image. Most face recognition systems use 2D images rather than 3D images for convenience. The software reads the geometry of the detected face. It identifies the features of your face, such as the distance from your forehead to chin, the depth of your eyes, contours of your eyes, chin and lips, the depth of your eye sockets, and the shape of your cheekbones. The result will be the signature of your face.

Step 3: Image conversion to data

The face analysis process generates digital information data based on your facial features. It turns your face signature into a mathematical formula. This code is called a faceprint, like a fingerprint or a thumbprint. And it’s unique for each face.

Step 4: Match finding

In this step, your faceprint is compared against the faces in a database. Then it is matched and identified.

The FBI in the USA has access to a database of more than 650 million face images. Any photograph tagged in Facebook becomes a part of the company’s database, which can also be used for facial recognition.

But the technology holds challenges that are causing many organizations and advocacy groups to resist or oppose it.

Problems with AI face Recognition Technology

Potential Breach of Privacy

Technology is supposed to be very helpful to track down criminals. However, it is vulnerable to misuse by governments for surveillance of private citizens.

Vulnerability in Detection

The recognition is not 100% accurate. The process can be easily off the mark because of changes in camera angles, appearance, and sometimes face position.

Massive Storage Data

The Artificial Intelligence used for face recognition technology needs big data storage, which is not available to all organizations.

Conclusion

With many applications in various fields, the future of AI-powered face recognition technology is promising. As governments worldwide regulate its application by alleviating privacy concerns and eliminating loopholes for potential misuse, the industry will see immense growth opportunities in applications for surveillance, finance, security, education, and healthcare.

InApp has been working on creating face recognition systems for many years. If you have any questions or would like a consultation, please contact us.

FAQs

What is the difference between face detection and face recognition?

Face detection is the detection of a human face in a photo or a video. Face recognition is the confirmation of the identity of the face that is detected.

Where is face recognition being used?

Law enforcement

Unlocking phones

Finding missing persons

Border controls

Airports

Banking

Improving retail experiences

Reducing retail crime

Healthcare

Marketing

Recognizing drivers

Tracking worker and student attendance

What is Fisherface?

Fisherface is one of the algorithms used for face recognition. It’s popular and is considered superior to other algorithms such as eigenface.

What is an LBPH algorithm?

Local Binary Pattern Histogram (LBPH) algorithm can recognize both the front face and side face in facial recognition software.

[isuperbinternetcollectorus]

Image Recognition in CPG Market Size, Share and Global Market Forecast to 2025 | MarketsandMarkets

According to market research report on "Image Recognition in CPG Market by Component (Hardware, Solutions & Services), Application (Inventory Analysis, Product and Shelf Monitoring Analysis & Gauging Emotions), Deployment Mode, End User (Online & Offline), and Region - Global Forecast to 2025”, published by MarketsandMarkets™, MarketsandMarkets forecasts the Image Recognition in CPG Market size to grow from USD 1.4 billion in 2020 to USD 3.7 billion by 2025, at a Compound Annual Growth Rate (CAGR) of 21.7 % from 2020 to 2025. Increased in the need for efficient and profitable retail execution processes with adherence to compliance standards and technological advancements to boost the adoption of Image Recognition in CPG Market across the globe during the forecast period.

 Browse and in-depth TOC on “Image Recognition in CPG Market”

231 – Tables

42 - Figures

209 - Pages

Download PDF Brochure@ https://www.marketsandmarkets.com/pdfdownloadNew.asp?id=162002756

Based on component, the hardware segment to account for the largest market size during the forecast period

This segment includes image sensors integrated with cameras. Hardware is an integral part of image recognition technology in the CPG market. Many companies like IBM and Qualcomm provide their company made sensors which help detect products, shelf life and even trends. For instance, Qualcomm offers the Vision Intelligence 400 platform that is built with powerful image processing and ML for smart camera products; it performs face detection, face recognition, product classification, and license plate recognition.

Based on application, the product and shelf monitoring analysis segment to account for the largest market size during the forecast period

The pandemic situation has forced people to concentrate more on online e-commerce businesses. Many leading retailers and CPG companies have adopted AI and image recognition technology for shelf monitoring and product identification. Computer vision and image recognition are used for product discovery, product recommendations and trend analysis.

Speak To Analyst @ https://www.marketsandmarkets.com/speaktoanalystNew.asp?id=162002756 Among regions, North America to account for the highest market share during the forecast period

North America is a significant contributor to the global Image Recognition in CPG Market. The US and Canada are the major contributors to the North American market. Canada and the US are increasingly witnessing the merging of artificial intelligence with image recognition and augmented reality; this is expected to drive market growth in the region. The United States is home to major AI-based image recognition companies, leading to increasing adoption of the technology across the region. As a result, many companies are making their move towards the US market, intending to develop an assemblage of AI capabilities.

The major Image Recognition in CPG Market vendors include IBM (US), Google (US), Qualcomm (US), Microsoft (US), AWS (US), Trax (Singapore), Catchoom (Spain), Slyce (US), LTU Tech (France), Imagga (Bulgaria), Vispera(Turkey), Blippar(UK), Ricoh innovations (US), Clarifai(US), Deepomatic (France), Wikitude (Austria), Huawei (China), Honeywell (US), Toshiba (Japan), Oracle (US).

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 Our 850 fulltime analyst and SMEs at MarketsandMarkets™ are tracking global high growth markets following the "Growth Engagement Model – GEM". The GEM aims at proactive collaboration with the clients to identify new opportunities, identify most important customers, write "Attack, avoid and defend" strategies, identify sources of incremental revenues for both the company and its competitors. MarketsandMarkets™ now coming up with 1,500 MicroQuadrants (Positioning top players across leaders, emerging companies, innovators, strategic players) annually in high growth emerging segments. MarketsandMarkets™ is determined to benefit more than 10,000 companies this year for their revenue planning and help them take their innovations/disruptions early to the market by providing them research ahead of the curve.

 MarketsandMarkets’s flagship competitive intelligence and market research platform, "Knowledge Store" connects over 200,000 markets and entire value chains for deeper understanding of the unmet insights along with market sizing and forecasts of niche markets.

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Content Source: https://www.marketsandmarkets.com/PressReleases/image-recognition-in-cpg.asp

Report: https://www.marketsandmarkets.com/Market-Reports/image-recognition-in-cpg-market-162002756.html

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Thermal Body Temperature Detection System

In recent years, our world has become a lot smaller and more become much more accessible. This is mainly due to advances in transportation technologies, such as aviation, becoming more affordable. This allows airlines to set up more travel routes than ever before.

 With new airline routes and air fares becoming more accessible, people now travel the world more freely and more regularly. However, this can also pose risks to countries and their people as travelers can introduce new illnesses and viruses into the countries they visit. In most cases, these illnesses and viruses cause a high body temperature, or a fever, which can be an indicator that a person is unwell and may need treatment.

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Biometric Time Attendance, Face Recognition Systems, Access Control Systems Dubai UAE. Access Control Security Systems, Face Recognition Systems

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UMIDIGI A7 Pro Global 4G Phone Quad Camera Andriod 10 6.3" FHD+ Screen 64GB/128GB ROM Octa Core Dual SIM Mobile Phone GPS OTG

1. Mediatek Helio P23 Octa Core CPU, 4xCortex-A53 2.0GHz + 4xCortex-A53 1.5GHz, good performance, combine with 4GB+64GB/128GB, run fast and stable. 2. 6.3 inch display screen, 2340 x 1080 pixel resolution, high clear and vivid color. 3. 16MP AI quad cameras: 16MP primary camera, F/1.8, 6-element lens; 16MP ultra wide angle camera, FOV 120 degree; 5MP depth camera; 5MP macro camera, 2cm macro distance??? 4. Photography function Ultra wide-angle mode, Steady handheld night photography, AI scenes detection, Macro mode, Portrait mode, Panorama mode, HDR, AI Beautify, Ultra wide-angle edge distortion correction, Dual LED flash, Face recognition, Real-time filters 5. Powered by 4150mAh high capacity battery, use for long time. 6. Both SIM slots are compatible with 4G, support 4G LTE in both slots simultaneously.  

1. Note: This Android OS Phone is designed only to work with the current Android OS installed in it. Any alterations such as upgrades or flashing a newer version will void the warranty. 2. The stated ROM amount shows the maximum available ROM with nothing installed. However, the Android OS and pre-installed software from the manufacturer will occupy some of this ROM. The available ROM on the device.

Network Operator (Parts of Countries) France Bouygues 3G, SFR 3G, Orange 3G, Free 3G, Bouygues 4G, SFR 4G, Orange 4G, Free 4G UK 3 3G, Orange 3G, T-Mobile 3G, Vodafone 3G, O2 3G, 3 4G, EE 4G, Vodafone 4G, O2 4G Italy 3 3G, Vodafone 3G, TIM 3G, Vodafone 4G, TIM 4G, Wind Tre 4G Spain Movistar 3G, Orange 3G, Vodafone 3G, Yoigo 3G, Movistar 4G, Orange 4G, Vodafone 4G, Yoigo 4G Russia MTS 3G, MegaFon 3G, Beeline 3G, VimpelCom (Beeline) 4G, MTS 4G, MegaFon 4G, Motiv 4G, Tele2 (Rostelecom) 4G, Vainakh Telecom 4G, Tattelecom 4G USA T-Mobile 3G, AT&T 3G, AT&T 4G, Plateau Wireless 3G, Union Wireless 3G, Viaero Wireless 3G, West Central Wireless 3G, U.S. Cellular 4G, Verizon 4G, Rock Wireless 4G, United Wireless 4G, Rise Broadband 4G, West Central Wireless 4G, Sprint 4G, Silver Star 4G, BIT Broadband (Wildfire) 4G, Bluegrass Cellular 4G, C Spire 4G, ClearTalk 4G, Colorado Valley Com 4G, ETC 4G, Evolve Broadband 4G, Infrastructure Networks 4G, iWireless 4G, Limitless Mobile 4G, Mosaic Telecom 4G, Nortex (SkyFi) 4G, PTCI 4G, PTC 4G, Speed Connect 4G, Space Data Corporation 4G Japan NTT DoCoMo 3G, SoftBank 3G, NTT DoCoMo 4G, SoftBank 4G, KDDI 4G

General Model A7 Pro Central Processing Unit(CPU) Mediatek Helio P23 Octa Core up to 2.0GHz RAM 4GB GPU ARM Mali G71 MP2 700MHz SIM Quantity Dual SIM SIM Types Nano SIM Card OS System Android 10 ROM 64GB/128GB External Memory TF card up to 256GB (not included) Sensor Ambient Light sensor, Proximity sensor, Acceleration sensor, Gyroscope, Compass, Fingerprint sensor Support Language Arabic, Bulgarian, Croatian, Dutch, Czech, Danish, English, French, Finnish, Filipino, Greek, German, Hungarian, Hebrew, Indonesian, Italian, Khmer, Malay, Latvian, Norwegian, Portuguese, Polish, Russian, Romanian, Swedish, Spanish, Turkish, Thai, UKrainian, Vietnamese, Simple Chinese, Traditional Chinese, Lithuanian, Slovenian Additional Features Face ID, FM Radio Fingerprint Rear-mounted

Network 4G FDD-LTE 700(B28A)MHz, 700(B28B)MHz, 700(B17)MHz, 700(B13)MHz, 700(B12)MHz, 800(B20)MHz, 800(B26)MHz, 800(B18)MHz, 850(B5)MHz, 850(B19)MHz, 900(B8)MHz, AWS-3(B66)MHz, 1700(B4)MHz, 1800(B3)MHz, 1900(B2)MHz, 2100(B1)MHz, 2600(B7)MHz 4G TDD-LTE 1880-1920(B39)MHz, 2010-2025(B34)MHz, 2300-2400(B40)MHz, 2570-2620(B38)MHz, 2496-2690(B41)MHz 3G TD-SCDMA 1880-1920(B39)/2010-2025(B34)MHz WCDMA 850(B5&B6&B19)/900(B8)/1700(B4)/1900(B2)/2100(B1)MHz 2G GSM 850(B5)/900(B8)/1800(B3)/1900(B2)MHz Type WCDMA, GSM, FDD-LTE, TDD-LTE WIFI 802.11 a/b/g/n, 5G Wi-Fi Signal / Wi-Fi Direct / Wi-Fi Display GPS Yes, GLONASS Bluetooth Yes, V4.0

Display Screen Size 6.3 inch Screen Type IPS, Capacitive Resolution 2340 x 1080 pixels Pixel Density 409PPI Multi-Touch Multi-point

Camera Camera Quantity 5 Front Camera 16MP Beauty Function Yes Back Camera 16MP+16MP+5MP+5MP Rear Flashlight Yes Video recording Yes Video Resolution 1080p, 720p video, 30fps

Media Format Audio MP3, WAV, AMR, AWB Video 3GP, MPEG-4 Picture PNG, BMP, GIF, JPEG

Connectivity Ports 1 x 3.5mm earphone port 1 x Type C 2 x Nano SIM card or (1 x Nano SIM card + 1 x TF card) slots

Battery Battery Capacity 4150mAh Battery Types Undetachable Quick Charge Yes Charging Power 10W

Dimensions & Weight Size 158.7*74.9*8.5 mm Weight 212g

Package Include Package Contents 1 x Phone 1 x User Manual 1 x Eject Pin 1 x USB Cable 1 x TPU Case 1 x EU Plug Power Adapter 

[safracatz]

How Artificial Intelligence Can Revolutionize Mobile App Development

If the mobile apps ecosystem penetrates deeper into us, it will certainly make us unrecognized. It has had an enormous influence on the gadgets since artificial intelligence development. Evaluation of the future, without the appropriation of artificial intelligence, hardly any mobile app would be created.

AI's far more than the technology of a single facet. It absolutely will impact a broad range of people as a multifaceted feature. Artificial intelligence functions at different levels, ranging from deep learning to natural language processing, advanced machine learning or advanced algorithms, including creating new or unique software, helping the user communicate with applications.

Whatever the phenomenon, even if someone is mobile without Artificial Intelligence and implements it, 100% is certain that they will not be able to contend with AI-enabled mobile applications. See how mobile app Development Company is revolutionized by Artificial Intelligence.

Impact of AI on the businesses

For the big retail giants like Amazon and eBay, Artificial Intelligence has already been an enormous success. For these businesses, that has proved to be the great potential. The services introduced in AI, Amazon Prime, have enabled Amazon Echo to be intimately involved in retail and logistics.

Artificial intelligence reflects and deciphered Artificial intelligence through the collected user databases so that a reliable, better user interface, and intuitive method can be further developed. Today, corporations use mobile apps powered by AI to get away from the competition. Most businesses want to use AI-powered technologies in the smartest way likely to achieve dedication and momentum.

Use of Chabot

The customer service companies are already using AI-enabled chatbots to answer all your customer's requests. 80% of companies use AI-powered Chabot in the survey carried out and is required to increase in 2020.

Improvement in the UX with voice and image     recognition

The identification of the voice and picture helps the users to use the mobile app development company simply by talking instead of typing which makes finding the images easier for the user. This not only increases the number of users but also increases the conversion rate. Instead of tapping, you must, for example, find a particular item.

Better security via Face detection

To unlock phones, identify license plates and private data they face recognition has already been used. Today developers plan to create a credit card that will pay the debts to the owner of the card. It will not be appropriate to swipe the coin.

Future of Artificial Intelligence-powered mobile apps 

Increased demand for AI-capable processors can also be used in growing AI applications, in increased cognitive processing, and also in mobile devices, which is attributed to the growth of the mobile AI market. Also, the market for edge-computing iOT's would increase with the cheap AI chips for the vision application and camera on mobile devices. It provides companies with an immense opportunity to sustain market growth.

Mobile app developers

Hire the developers of mobile apps as AI has traditionally changed mobile app growth. Mobile app developers understand automated learning extensively. You can deploy the productive code with numerous options. They are creative and flexible, so they are sufficiently competent to change how mobile users access and collect data.

Conclusion

The mobile app industry adds greatly to artificial intelligence. For mobile application growth, there are many advantages of artificial intelligence and a lot more details are involved. AI would help many businesses with user-friendly UIs to produce full revenues. Stay up-to-date and upgrade and advance smart AI-driven applications to eventually expand your business. You may get in touch with us at Best mobile App Development Companies in Canada for a free quote to develop a mobile app for your business. And helps Business owners to reach more customers who want to change their business towards app development, Blockchain, and Machine Learning Development software. The Company has a very good working environment. To know more about my company, Visit Fusion Informatics. For more queries please send a mail to get a free quote sales@fusioninformatics.com.

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[appliancesreviews]

Google Pixel phones Review

Of course, today innovative technologies are the dominant trend in the consumer electronics segment. This process began with the digital revolution at the end of the last century. As a result, colossal consumer demand stimulates fierce competition, forcing market leaders to actively develop new technologies. In fact, innovative technologies have become a necessary requirement for the competitiveness of any technically sophisticated device. Today, even relatively simple devices, including Samsung Dual Cook Flex Oven, Hurom H-AI self-feeding slow juicer, bladeless Dyson Pure Cool Purifying Tower Fan, etc actively use innovative solutions. But most clearly it manifests itself in high-tech devices, including PCs, TVs, projectors, etc. Of course, a modern phone leads in this list. In fact, the modern smartphone has become a universal pocket PC with fairly high-quality media functions, including a camera, projector, etc. For example, companies already offer projector mobile phones with a projector function, including the very popular Blackview MAX 1 Projector Mobile Phone. Moreover, modern multi-camera phones provide excellent quality shooting in almost any environment. In fact, functionality has become one of the main criteria when choosing a smartphone.

Google phones

Of course, Google, one of the innovative leaders, did not want to stay away. In 2010, the company introduced the Nexus series. These models were produced by various companies, including HTC, Samsung, LG, Huawei, Motorola, etc. As a result, almost identical models had different names: - HTC Desire - Google Nexus One; - Samsung Galaxy S - Google Nexus S; - Samsung Galaxy S3 - Google Galaxy Nexus; - LG Optimus G - Google Nexus 4; - LG G2 - Google Nexus 5. Ultimately, the company effectively solved this problem by abandoning the idea of smartphones for developers. In 2016, at a presentation in San Francisco, the company introduced its first Pixel and Pixel XL smartphones. And on September 21, 2017, Google announced an agreement with the Taiwanese HTC Corporation, which has been producing smartphones based on Windows Mobile (Microsoft) and Android since 2009. Of course, the OS is the main pros of this brand in terms of the availability of updates. For example, the latest Android Q (or Android 10) today is available only to owners of Pixel smartphones of all generations. Today, Google offers the most simple and clear classification of its phones in the range from the first to fourth generation in two modifications of the screen size. The first generation Pixel and Pixel XL use 5-inch and 5.5-inch Amoled displays with a resolution of Full HD (441ppi) and QHD (534ppi), 32 / 128GB, RAM 4 GB (LPDDR4) and a quad-core 64-bit ARMv8-a (2, 15 GHz + 1.6 GHz). Unfortunately, in December 2019 Google notified the termination of their support. Accordingly, their owners will not have access to further Android updates.

Pixel 2 and 2 XL, 3 and 3 XL, 3a and 3a XL

Already in October 2017 the company introduced the second generation of Pixel. They use a 5-inch Amoled with 1080 × 1920 resolution and a 6-inch P-OLED with 1440 × 2880 resolution. In addition, the models use Qualcomm Snapdragon 835 processor, 64 / 128GB and RAM 4 GB (LPDDR4). As known, the Qualcomm Snapdragon 835 chipset has become top-end for 2017 smartphones. It uses 2 clusters, including 4 Kryo 280 (Cortex-A75) with a frequency of 2.45 GHz and energy efficient (4 Kryo 280 with a frequency of 1.9 GHz). Initially, the company supplied these models with Android 8.0, which was later updated to Android 9.0. In October 2018, the third generation was introduced, traditionally including the Pixel 3 and Pixel 3 XL with Android 9.0 Pie. The company increased Amoled displays to 5.5 inch with 2160 × 1080 resolution and 6.3 inch with 2960 × 1440 resolution. In addition, Google upgraded the chipset to Qualcomm Snapdragon 845 (4 Kryo 385 (Cortex-A75) with a frequency of 2.8 GHz and energy-efficient 4 Kryo 385 with a frequency of 1.8 GHz). The memory has not changed (64 / 128GB, LPDDR4 RAM 4 GB). In addition, in May 2019, the company introduced the Pixel 3a and Pixel 3a XL as the budget modification of the third version. They have the same cameras, a 5.6-inch (2220 × 1080) and 6-inch (2160 × 1080) Amoled display, but use the new Qualcomm Snapdragon 670 with 8 Kryo cores for mid-budget smartphones (2 Cortex-A75 with a frequency of 2.0 GHz and energy-efficient 6 Cortex-A55 with a frequency of 1.7 GHz).

Pixel 4 and Pixel 4 XL

On October 15, 2019, the company introduced its latest fourth generation, including the Pixel 4 and Pixel 4 XL. These models are already running Android 10, using UFS 2.1 memory, a 5.7-inch screen with 2280 x 1080 resolution (444 ppi) and a 6.3-inch screen with 1440 x 3040 resolution (537 ppi). Smartphones support an Always-On display, automatic brightness control, color temperature adjustment, and a refresh rate of 90 Hz. This generation uses the 7nm Qualcomm Snapdragon 855 (Kryo 485 with a frequency of up to 2.84 GHz, 3 Kryo 485 with a frequency of up to 2.42 GHz, 4 Kryo 485 with a frequency of up to 1.78 GHz). In addition, the company has expanded RAM to 6 GB. The latest generation uses the voice-to-text, the live subtitles in any program, and built-in radar for gesture control (Motion Sense). In addition, the models support unlocking based on a 3D face map. But Google has better implemented this option compared to Apple. iPhone constantly scans the face and often locks the phone when changing the viewing angle or dim lighting. Pixel 4 determines the face much more reliable, regardless of lighting and viewing angle. In addition, it's faster even compared to Samsung. The innovative Motion Sense uses the Soli radar to detect movement without a camera. In fact, function provides only non-contact rewinding the tracks and videos in any programs, and adjusting the alarm volume. Apparently, in the future, the company will expand the Motion Sense functionality. Today it's available only in the USA and some European countries.

Key features

Today, experts most often note the following key features of new models. 1. Android without third party apps improves the correctness of work, but reduces the functionality. 2. The battery capacity of 2800 mAh and 3700 mAh is inferior to Samsung and Apple. Even with a small load, battery life does not exceed one day. 3. Failure from the fingerprint sensor is still perceived as a controversial decision. Apple was the first to refuse this option, but all Android smartphones continued to use it. Apparently, its relevance will finally be determined in the next few years. 4. Pixel 4 has a RAM of only 6 GB, compared with 8-12 GB in flagships of other companies. On the other hand, today many experts doubt the appropriateness of its further expansion. As known, RAM serves the core (Linux for Android), drivers and modules of core. In addition, RAM stores virtual files, data for IMEI and modem settings, and for graphics adapter operation. Modern OS reserves about 1 GB for these tasks. Multitasking for 5-7 apps requires about 700-900 MB. Launching new apps requires another 300-400 MB. Thus, even 3 GB RAM effectively ensure the phone operation in any mode. Maybe Google risked stopping the marketing race of ramp-up RAM.

Conclusion

Motion Sense, Soli radar, voice-to-text, live subtitles, etc allow the fourth generation of Pixel phones to claim a worthy place in the list of innovative leaders in 2019. But access to Android updates continues to be their main competitive advantage. However, the price / quality ratio of Pixel phones also corresponds to a fairly high level, allowing them to successfully compete in the market. This video offers the Google Pixel 4 XL vs iPhone 11 Pro Camera Test. Read the full article

[lancecarr]

Seismic Rumblings In Video Production

A view of Cine Gear 2019 at Paramount Studios.

Video/digital cinema production in 2019, to me, feels as if there are some groundbreaking changes underway. I’m not sure if you have felt this lately, but I definitely have.

BMD Resolve 16.1 public beta has some interesting Ai features that are supposed to preemptively help editors cut more efficiently.

Seismic Change #1 – Has Ai Finally Arrived in Editing?

As you may or may not be aware of, Blackmagic Design had major new product announcements recently. Buried within those new announcements was word that Resolve 16.1 public beta has been released. Contained within Resolve 16.1 is the new Smart Indicator. The new cut page in DaVinci Resolve 16 introduced multiple new smart features, which work by estimating where the editor wants to add an edit or transition and then allowing it to be applied without the wasted time of placing in and out points on the exact locations of the clips. While I’m not positive, I believe that the language Blackmagic Design is using indicates that these new features are at least a basic form of Ai, in that the software anticipates some editing decisions that the editor might want to make and then does them.

This is supposedly faster because the software guesses what the editor wants to do and just does it by adding the inset edit or adding a transition to the edit closest to where the editor has placed the CTI. The problem is in complex edits, where it’s hard to know what the software would do and which edit it would place the effect or clip into. This is where the new smart indicator provides a small marker in the timeline so customers get constant feedback on where DaVinci Resolve will place edits and transitions. The new smart indicator constantly live updates as the editor moves around the timeline.

The Boring Detector in Resolve 16.1 public beta is supposed to alert the editor if their timeline doesn’t have enough edits and it also helps to detect jump cuts.

The other feature notable in Resolve 16.1 is the Boring Director. DaVinci Resolve 16.1 introduces a new Boring Detector that allows the whole timeline to be highlighted where any shot is too long and would be boring for a viewer to watch. The boring detector can also show jump cuts where shots are too short as well. The analysis is constantly showing which parts of the timeline are boring so as editors work and add shots to their edit, they can see the remaining parts of the edit that are considered boring. The boring detector is great when using the source tape, as editors can perform a lot of edits without playing the timeline, so the boring detector will be an alternative live source of feedback.

The question is, how do you feel about your editing software functioning as a sort of Ai powered assistant versus a passive tool? For me personally, I’m all for it. If I’m editing a piece, in the end, all that matters is if the edit works and if the visual and narrative story is engaging. I don’t really care that much about the process of how I got there. All that matters to me is if my clients and the audience like what they see. However, keep in mind, editing, for me, is a means to an end. I’m not a full-time editor who only edits for a living; it’s just a component of what I do. If I was a full-time editor, I might feel differently. Or I might not. How do you feel about this development from Blackmagic Design?

The Impending Death of the Camera is reflected in the numbers tracked by the Japanese camera industry organization CIPA. The numbers are grim—the average consumer is no longer buying cameras but are using their smartphone camera more than ever before.

Seismic Change Number #2 – The Death of the Camera

If you haven’t heard about this, you will be soon. I won’t go into all of the detailed analysis because that would probably be pretty boring to read, but let me glean a few headlines for you about what’s been happening in our industry:

Since 2010, the worldwide camera industry has dropped off 84 percent in sales volume over the past 9 years.

There was a 24 percent drop in the number of cameras shipped in 2018 from 2017.

Canon and Nikon saw camera sales fall more than 17 percent for the first quarter of 2019 compared to the first quarter of 2018.

Global digital camera shipments in February 2019 came in at only 935,148 units compared to the 1,001,398 shipped in January 2019. This is a more than a 30 percent decrease year-over-year.

What conclusions can we draw from these numbers? Keep in mind that these statistics and numbers are global and that they focus more on consumer cameras than professional digital cinema cameras. It’s obvious that the majority of the camera market hasn’t disappeared, but it has changed platforms, obviously to smartphones. A lot of buyers who would have previously just bought a digital point-and-shoot now are just using the increasingly capable cameras in their phones. The cameras in the highest-end smartphones especially have grown to be better and better as far as image quality and features.

As a consumer of professional cameras, why should all of these numbers concern me? The problem is, we have a trickle-down effect at work here. Canon USA recently laid off a sizable amount of its workforce and closed their Jamesburg, New Jersey, service facility. Sony has been dragging their feet, not introducing any new digital cinema camera in 2019, although they did introduce the Venice in 2018. Panasonic did introduce a new mirrorless 6K camera, the S1H, at CineGear 2019, but no new digital cinema camera from them this year either. Nothing but a $6k price reduction on their older Varicam LT.

As you can plainly see, the massive shrinking of the consumer camera market is affecting the professional digital cinema camera market as well. We’re also seeing the encroachment of the Chinese into the pro digital cinema camera market with new cameras like the Z Cam E2 and the Kinefinity Mavo. Both of these manufacturers are offering features and specs that were recently only available on the very top of the line cameras like the RED lineup, but for a fraction of the cost.

Is the camera market actually dying? I guess that depends on how you view the camera market. For traditional camera manufacturers, yes, this is a very difficult time as sales volume has dropped off tremendously. For professional users, we’re facing much longer product refresh cycles compared to the frantic pace of new cameras and innovation over the last few years. For some of the newer and smaller players, the camera market worldwide still presents opportunities to flourish, but the rules of the market and what the customers expect are changing rapidly. Witness Blackmagic Design who just introduced their new Pocket Cinema 6K camera at $1,500 less ($2,495) than Panasonic’s S1H 6K camera that isn’t even shipping yet. Stay tuned to see what craziness will envelop camera buyers next.

Disney Plus is the next big thing in streaming services from the hungry media conglomerate.

Seismic Change #3 – What’s Happening to Filmed Entertainment? 

In a nutshell, consolidation, competition and streaming ascend. Consolidation is really all about the D-word, Disney. Is there anything that the Disney monolith hasn’t yet swallowed? Star Wars? Check. Pixar? Check. Marvel? Check. Fox? Check. Next up is the launch of the Disney Plus streaming service that will go head to head in the marketplace with Netflix and with Apple’s upcoming TV Plus streaming service. The players are changing as traditional studios like Sony, Paramount and Warner Bros. are being somewhat passed over by these new streaming monoliths. Sure, the old “traditional studio” players will still be around and providing content for the new players, but the days of theatrical and episodic television over broadcast being considered “Hollywood” are drawing to a rapid end.

What does all of this mean for us content creators? It’s hard to say. All three streaming services will have a huge appetite for new original and derivative programming, which is good for us. The competition is intense, though, as almost everyone is now more interested in pitching content to the new players than the older established studios, so it’s not like there’s a huge welcome mat on the front door of each streaming service inviting you in to pitch your series, movie or web series.

I predict a wholesale shakeup in the kind of programming that will be popular though. In the era of streaming, it feels as if the audiences will have more to say about the kind of content they watch since they’re more in charge than they were in the previous era. Audiences today aren’t afraid to activate a streaming service just for watching a particular series or event, then turning their subscription to that service off before moving on to the next show, series or outlet. There’s very little loyalty to a single streaming service like there used to be for watching “must-see TV,” so the landscape is becoming more fractured and individualized.

There have been some bright spots: The global theatrical and home entertainment market generated $96.8 billion in 2018, a 9 percent increase on 2017, according to a new report from the Motion Picture Association of America (MPAA). As you’re probably aware, gaming surpassed filmed entertainment about 15 years ago and ever since then, filmed entertainment has been on a long, slow downward trend, so seeing that much year-on-year growth is encouraging for us all. Here’s to that number increasing! 

The post Seismic Rumblings In Video Production appeared first on HD Video Pro.

https://www.hdvideopro.com/blog/seismic-rumblings-in-video-production/

[android-app-development-company]

Why AI is the Secret to Mobile App Success?

Nowadays smartphone is an indispensable tool rather than a luxury item for everyday life, peoples have trust in mobile apps for shopping, banking, entertainment, maintaining, health, fitness and many more. In 2019 the mobile phone users will be expected to pass 5 billion and the number of mobile apps is growing at a rapid pace. So to survive in the tougher App store mobile apps should offer something extra for customers. Here it comes AI (Artificial Intelligence), which is a widely used technology to enhance mobile apps and make them different from the rest.

AI means a whole new level of intelligent mobile app personalization and it has become a vital part of the technology industry. This the ability of machines to perform without human instruction is led to the rapid growth of AI mobile applications, which will help to succeed in many business activities with greater accuracy and at a fraction of time.

Some highlights of AI with mobile apps are the following

•    Face unlock

•    Translating Languages in Real-Time

•    Camera subject detection

•    Voice search

Why AI is important for a Mobile App

Helps in Prediction

AI predictive algorithm will use the customer’s previous purchase history to predict what a customer will wish to buy and also it will detect if the customer did any unusual payment and notifies the customer. The main motive for this predictive AI app is that it will increase the revenue of the business.

Optimizing the User Experience (UX)

Mobile Apps automate everywhere in humans life from Augmented reality to cab apps to support. Google lens is the best example, it showing AI apps will make every task much easier. We can use this to point camera on anything and the application will provide the relevant information about that.AI will give excessive user experience to the customers and it will increase the user engagement.

Natural Language Generation (NLG)

NLG means the machine can understand human languages in a smart way. It is true that many app developers have limited exposure for natural language understanding but here AI offering incredible outcomes.

NLG and cloud solutions are mainly useful for the journalism industry. This will help to create stories based on data by using NLG robojournalisam programs. This will increase the overall performance of the app.

Learn user’s behavior patterns

Natural Language Processing (NLP) combined with Machine Learning offers a realistic interaction with the users. This will help to understand the user's behavior pattern for seamless interaction. Netflix is the best example they are using ML for gathering data about the user’s past behavior.

Conversational User Interfaces (CUI) for better communication

CUI will make speech recognition more powerful for better communication. It will simplify communication between users and product through voice interfaces and messengers and communication will be more truthful, informative and relevant. Mostly Finance and Management Apps are using this.

Offering automated reasoning

Automated reasoning will help to solve the problems more quickly and accurately to increase productivity. Taxi apps are the best examples for this they can choose the shortest way based on other cab drivers to travel details

Conclusion

Today mobility is growing at a breath-taking pace, So integrating AI with giving more productivity in a short time period.DxMinds is the leading Mobile App Development Company in Sri Lanka, Singapore, India, and USA provides high-quality AI app development services based on your business requirements. Our app developers are experts in all new technologies like AI, Machine Learning, Chabot, Block Chain, React Native, IOT and many more to provide better digital transformation services to your business.Our regular technology updating and on time services placed us as the best apps development company in Sri Lanka.

If you wish to integrate AI with your business mobile apps for more tangible results

Contact us on info@dxminds.com

India:+91–7483546629

USA: 1 (833) DxMinds (396.4637)

 Visit: Mobile App Development Company in Sri Lanka, Colombo

[click2watch]

GM, BMW Back Blockchain Data Sharing For Self-Driving Cars

Car giants General Motors and BMW are backing blockchain tech as a way to share self-driving car data among themselves and other automakers.

It’s all part of a bid to unlock valuable data held in silos which will ultimately get autonomous vehicles on the road sooner. Exploratory work in this area is being done under the auspices of the Mobility Open Blockchain Initiative (MOBI), a consortium formed last year to harmonize the development of distributed ledger technology (DLT) across the car industry.

CoinDesk has learned that the next MOBI working group on so-called autonomous vehicle data markets (AVDM) will be chaired by General Motors (GM). The automaker has clearly been thinking about using blockchain to share data for some time, having filed a patent detailing such a system for fleets of self-driving cars at the end of last year.

The new AVDM working group chairman Michal Filipowski, manager global innovation of General Motors, told CoinDesk in an email:

“I am excited to chair the AVDM working group and kickoff the development of our collaborative efforts with the other OEM [original equipment manufacturers] and supplier MOBI members.”

And notably, BMW, a founding member of MOBI, has also expressed its interest in the data-sharing use case for the first time. (Previously BMW tested blockchain to track mileage of leased vehicles.)

The German manufacturer, like many others in the auto space, has realized that keeping self-driving data in silos is a “major barrier” to widespread adoption of autonomous vehicles.

“With the advent of blockchain, decentral[ized] data management can be implemented in a privacy-preserving and efficient way,” Andre Luckow, blockchain lead at BMW Group, told CoinDesk. “Further, emerging technologies, such as decentral machine learning, secure multi-party confidential computing, and decentral data markets, will provide the fabric for data processing in the autonomous age.”

Stepping back, the push to foster autonomous vehicles faces a key hurdle: the sheer volume of data self-driving cars must consume in order to “learn” how to drive in different places and scenarios. Driving around a test track is one thing, but negotiating a busy city center on a rainy day is quite another.

Crown jewels

According to a Rand Corp report, getting to the stage where AVs are safe in all conditions could take hundreds of billions of self-driven miles, a process by which data are gathered using cameras and Lidar (a detection system which works on the principle of radar, but uses light from a laser).

Pooling this data together to train artificial intelligence on might seem like a no-brainer, but autonomous vehicle companies – be they carmakers or Uber or Google-affiliated, Waymo – tend to think of their self-driving data as their crown jewels.

This is where blockchain comes in, explains Sebastien Henot, head of business innovation at the Renault-Nissan-Mitsubishi Alliance Innovation Lab in the Silicon Valley (who chairs MOBI’s vehicle identity working group). He told CoinDesk:

“The old fashioned way is that everybody thinks their data alone is so precious. The new way is to consider data sets like cooking ingredients: you need to be able to mix multiple ones to create something really valuable. Data marketplaces call technically for blockchain because you can create an environment where rules are clear in terms of who shares what data with who.”

Another MOBI member, Ocean Protocol (which went live Monday), is focused on the creating blockchain-based data markets and running a shared AI on them. Ocean co-founder Trent McConaghy is aiming to create a kind of enterprise data commons where everyone can benefit, yet at the same time, this data can be prevented from escaping beyond the firewalls of any one company.

McConaghy explained that Ocean takes “federated machine learning” (machine learning built without direct access to training data, where data remains in its original location, such as on a smartphone, for instance) and gives it an additional dose of decentralization.

Google and others have been “pushing pretty hard on centralized federated learning,” said McConaghy, where they control the whole process.

“The makes the holders of the data feel pretty uneasy. So if you can actually remove that creepiness and the process of learning if done from silo to silo to silo in a decentralised fashion, that is much better. Decentralised federated leaning is what Ocean unlocks,” he told CoinDesk.

And this more decentralized approach is what BMW and GM, as part of AVDM group at MOBI, seem to be enthusiastic about.

Michael Ortmeier of BMW Group IT communications said Ocean’s approach to data sharing is one the company is “following with great interest.”

“We used the opportunity of the MOBI colloquium to speak with Ocean and other members and we will definitely continue and intensify these discussions,” he said.

Waymo data

It’s no secret that Waymo, the self-driving technology development company owned by Google parent Alphabet, is further ahead than anyone else in terms of how much data it has collected.

However, if you run the numbers, says Chris Ballinger, the founder and CEO of MOBI, it could still take many years for Waymo get there on its own.

Ballinger, the former head of mobility at Toyota, estimates that Waymo is accumulating a million miles of self-driven miles a month, adding:

“So you can say in miles it’s going to take millennia. Something has to be done and obviously it will speed up as more cars get on the road. Once everybody gets involved and once they start sharing it will be an order of magnitude increase.”

However, Vint Cerf, vice president and chief internet evangelist for Google, countered the claim the Waymo might way off when it comes to reaching its AV goals.

It depends what you mean by “driving data,” said Cerf. “We have billions of miles in simulation by generating direct inputs into the software that emulate what the sensors see,” he told CoinDesk by email.

Regards the possibility of car companies using blockchain networks to share data, Cerf added:

“I do not see additional value in the overhead of blockchain vs digital signatures.”

Toy car traffic image via Shutterstock

This news post is collected from CoinDesk

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