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industryuptodate · 4 years ago

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Global Automated Passenger Counting System Market Analysis of Company Stocks and Strategic Development 2021-2027

Syndicate Market Research (SMR) has added the latest and fresh report on "Global Automated Passenger Counting System Market by Key Manufacturers, Regions, Type, Application and Forecast to 2026."

2021-2026 Global Top Countries Automated Passenger Counting System Market Report

The detailed and latest study report entitled "Global Automated Passenger Counting System Market 2021" presents professional and up-to-date information on the global Automated Passenger Counting System industry. This report covers market outlook, forecast, and analysis on the worldwide and regional levels. Furthermore, The report also analyses the market based on its investment feasibility and attractiveness. It also provides a useful description of every phase and rising industry trends. This study report will permit the readers to focus on the Automated Passenger Counting System market product description, current competitive players in the market and the market revenue with profitability. Global industry analyzes the market with the guide of its Type such as (Infrared, Stereoscopic Vision, Time-of-Flight, IP cameras), Leading Players, Regions, and Applications/end users like (Buses, Trains, Ferry Boats) of the market, forecast up to 2026.

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The Scope Of The Report Is As Follows:

This report analyses the scope of the Automated Passenger Counting System market. This can be achieved by using previous historical statistics, studying qualitative insights in detail, probably projections about worldwide market size. The projections showed in this Automated Passenger Counting System report are taken from formerly proved research methodologies and hypotheses. By performing such projections, the market studies document serves as a storehouse of evaluation, records, and data for every aspect of the Automated Passenger Counting System market. Considering the geographic regions, the market is split into various regions like North and South America, Europe, Middle-East and Africa, Asia-Pacific.

To help key decision-makers, the report includes a competitive depicting of the leading players in the Global Automated Passenger Counting System market, tempting investment plans, market positioning of important manufacturers sections. The Top Manufacturers/Prime Players covering the Global Automated Passenger Counting System Market (2020-2026) are; Ris-GmbH (Germany), HELLA Aglaia Mobile Vision GmbH (Germany), Eurotech S.p.A. (Italy), DILAX Intelcom GmbH (Germany), Infodev Electronic Designers International Inc (Canada), Cisco Systems (U.S.), Siemens AG (Germany), Hitachi (Japan), Huawei Technology Co (China), Clever Devices Ltd (U.S.), Retail Sensing Ltd (U.K.), Syncromatics Corp (U.S.), Trapeze Group (Canada).

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Regional Analysis of Global Automated Passenger Counting System Market (2020-2026):

1. Europe (Germany, France, UK, Russia, Italy) 2. North America (The United States, Canada, Mexico) 3. Asia-Pacific (India, China, Japan, Korea, and South-east Asia) 4. South America, Middle East, and Africa.

Global Automated Passenger Counting System Market report particularly covers 11 Chapters. They are as follows;

Chapter 1 offers us Introduction, market overview, product scope, market possibilities, market driving force, and market chance; Chapter 2 presents market forecast, by regions, application, and type, with revenue and sales of Automated Passenger Counting System market, from 2020 to 2026; Chapter 3 and 4, to describes the challenging condition of the top manufacturers, with income, deals, and market share of Automated Passenger Counting System market in 2016 and 2019; Chapter 5 suggests the top producers of Automated Passenger Counting System, with revenue, price, and sales, from 2016 to 2019; Chapter 6 and 7 indicates the market with market share and growth rate by type, application, from 2012 to 2019; Chapter 8 covers the global Automated Passenger Counting System market by regions, with income, market share, and sales, for each region, from 2020 to 2026; Chapter 9 offers the global Automated Passenger Counting System market key areas, with sales, market share, and revenue by key countries in those regions, from 2016 to 2019; Chapter 10 and 11 provides details about investors, distributors, sales channel, dealers, research discovery and conclusion, appendix and facts source;

What Automated Passenger Counting System Market Research Report Offers:-

1) The all-inclusive analysis of the worldwide Automated Passenger Counting System market. 2) Assessment of market development. 3) Comprehensive innovation in the market. 4) Share investigation of Automated Passenger Counting System industry. 5) Market essential methodologies of predominant makers. 6) Entire information about Segmentation details of the Automated Passenger Counting System market. 7) Advancement of industry segments and regional markets. 8) Endorsement to firms to set up/settle in their specialty inside the market.

The end of the Automated Passenger Counting System market report gives you a perception regarding the global business research findings and conclusion that assist you to create valuable market strategies to accomplish competitive benefits.

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aianalytics · 4 years ago

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3 enterprise AI success stories

Artificial intelligence (AI) and machine learning (ML) might be high in the hype cycle at the moment. But that doesn’t mean organizations are not realizing tangible gains from deploying products that leverage the technologies.

Here are three examples of how AI and ML are improving internal business processes and paying off for enterprises.

Boosts for sales and marketing

Beacon Street Services needed to have a “single source of truth” for all its company’s data, to ensure consistency and accuracy across its applications. The company is the services arm of Stansberry Holdings, which produces financial publications exclusively through purchased subscriptions.

Having collected and stored massive volumes of data using Snowflake, the cloud-based data warehouse service, Beacon Street Services wanted to use that data to help its sales and marketing teams improve on previous tactics and processes of selling subscriptions.

“Our marketing and sales teams saw an opportunity to improve on sales processes by applying a data science approach,” says David Kline, vice president of engineering at Beacon Street Services. “With this approach, we hoped to better identify buying criteria to help the marketing team run more effective campaigns.”

Taking the historical user data the company had in its Snowflake data warehouse and loading it into an enterprise AI platform it deployed from DataRobot beginning in 2019, it was able to build a series of models quickly and automatically, using dozens of the latest data science algorithms. With these models, it identified buying criteria to help the marketing team run more targeted and effective campaigns.

The company now continues to feed large amounts of data into the AI platform from the data warehouse, Kline says.

As a result of the new process, Beacon Street Services saw a 10% increase in sales and is on track to realize $15 million in additional annual sales directly attributable to the AI platform. Since implementing the platform, the company has seen 30 to 35 times return on investment in revenue gains and cost decreases, Kline says.

“For example, for one individual project we had to manually go through previous transactions to determine the risk of chargebacks following automatic subscription renewal and create a risk evaluation model, Kline says. “Not only was this process automated using AI, but we now have the benefit of proactively handling upcoming transactions.”

In addition to seeing improved accuracy and optimized marketing campaigns using AI, the DataRobot platform also provided significant time savings. Previously, it would take as long as six weeks to develop a model, with no guarantees that the optimal algorithm was selected. With the enterprise AI platform, that time to develop and deploy models that used more appropriate algorithms was reduced to just one week.

A side benefit is that the company’s IT team is spending less time analyzing data and more time working on potentially valuable projects for the business.

Classifying documents for better security

Company Nurse, which provides Covid-19 health screenings, workplace injury reporting, and nurse triage services for employers, is leveraging AI on several fronts.

One project involves enhancing the process of classifying documents. Company Nurse in 2020 deployed a platform from Concentric called Semantic Intelligence, to protect private workers’ compensation data on behalf of its customers and their end users.

The system autonomously discovers Company Nurse’s critical unstructured data, providing an opportunity to mitigate data sprawl and reduce threat surfaces.

As part of its service to customers, Company Nurse completes incident reports for workers’ compensation, providing appropriate care advice to injured workers and managing providers for referral. The information in the reports and forms includes significant amounts of unstructured data, says Henry Svendblad, CTO at the company.

By using the AI-powered system from Concentric, Company Nurse can protect private information in the documents without the need for staff to manually go through the data. The platform automates unstructured data security using deep learning to categorize data, uncover business criticality, and reduce risk.

Semantec Intelligence uses the baseline security practices seen for each category of data to calculate a “risk distance” from the baseline for each individual document. The risk distance uncovers events such as inappropriate sharing of information, risky storage locations, and incorrect classifications.

Not long after deploying the platform, Company Nurse was able to identify duplicate files it didn’t need to maintain, and found opportunities to enhance access permissions, Svendblad said. The company also found a large cache of private injury reports that were left on an open share application due to oversharing and lax access permissions.

“Any leakage of these documents would have been devastating to Company Nurse,” Svendblad says. “We have closed several small ‘blindspots,’ where files have been overshared, thanks to [AI] automatically classifying these documents for us. Preventing a single breach is worth tens of thousands [of dollars] to us. The cost of the solution is well worth the ROI—even if not a ‘hard’ ROI.”

In addition to the document classification process, Company Nurse is also applying AI-powered software products to functions such as sales opportunity scoring, data analytics, identification of zero day security threats, and speech-to-text transcription.

It’s difficult to estimate the investments the company has made in AI technologies because the tools are built into various software products it’s using, Svendblad says. But the company has seen multiple benefits, including improved security, enhanced work/life balance for employees, and improved quality of service in its contact center.

A step toward autonomous oil drilling

Oil and gas companies are under growing pressure to increase the efficiency of their drilling operations. One such company, Devon Energy, is in the early stages of leveraging AI and ML capabilities for real-time decision making that could potentially lead to closed-loop automation capabilities—or an autonomous drilling rig at each well site that would help to boost overall operations, efficiencies, and safety at the sites.

Devon Energy, which recently merged with WPX Energy (the company that initiated the push to AI/ML beginning in 2020), is using an offering called Hivecell to deliver edge computing at its drilling sites on oil fields in West Texas and North Dakota. Hivecell, provided by a company of the same name, is an “edge-as-service” offering that enables computing and analytics close to the source of the data.

The data is created by sensors in the equipment provided by a service company that Devon Energy uses for hydraulic fracturing processes. The data is transferred from the sensors to the service company’s systems and then is sent from those systems to Hivecell via the TCP/IP protocol.

Devon Energy is in the first phase of leveraging Hivecell to process machine learning at the remote well sites. Having this capability will enable Devon to avoid sending all of the data to the cloud for processing, which is costly and slow. Hivecell is used in conjunction with Confluent’s event streaming platform that manages the raw drilling site data from Apache Kafka.

“We’re always searching for ways to improve our drilling and completion operations efficiency,” and are looking to automate manual tasks through ML, says Dingzhou Cao, senior data science advisor at Devon Energy. The first phase of the project involves gathering real-time data on hydraulic fracturing, a well-stimulation technique involving the fracturing of bedrock formations by a pressurized liquid, so that natural gas and petroleum can flow more freely.

“We are in the process of building models to detect the hydraulic fracture events from real-time data automatically,” Cao says. “We wanted to be forward-thinking and are always looking for ways to build efficiencies and improve processes.”

Typically, oil and gas companies today rely on cloud computing services for processing and analyzing data from remote locations in near real time, Cao says, but this has the disadvantage of internet connection instability and latency issues.

“Think of a self-driving car that is processing data in the cloud,” Cao says. “Every millisecond counts when it comes to the vehicle reacting, to ensure the safety of the passengers and those around it. So, the amount of time it takes to send the data from the car to the cloud is crucial and could lead to safety incidents if it’s not in true real time.”

The same is true for closed-loop optimization; for example, auto-drilling rigs at the well sites. “We need to be able to react in real time, and can’t risk data being lost due to an unstable internet connection,” Cao says.

Devon Energy is building the foundation for true real-time, analytics-driven decision making, and eventually closed-loop control of the well sites. This will eventually allow the company to use edge-based stream processing for real-time, closed-loop control over drilling operations. The data streams produced by the machine learning models and analytical preprocessed data at the well site will also be replicated to the cloud for other purposes.

“Given that Hivecell runs on-site, we don’t have to worry about latency or internet instability issues,” Cao says. The platform will allow Devon to easily deploy, manage, and scale ML models at the well sites, he says.

Devon Energy hopes to complete the first phase in 2021 and then move to the second phase, in which it will determine the analytics models based on the most crucial business needs.

Although Cao did not provide specific cost information, he says the implementation is cost-effective compared with using a cloud-based option. “By leveraging Hivecell, we’re able to process the data on the stack and don’t need to pay the software licensing fee for a similar stream processing engine,” he says.

With the implementation, “we’re putting real-time data in the hands of who needs it most, when they need it most,” Cao says. “Our engineers have the ability to access the real-time data via their cell phones or computer. While we’re still in the first phase, which is just focused on capturing this data, as we move through future phases the analytics model will be used to aid well site decision making.”

#AI #ML #cloud

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humans-are-seriously-weird · 8 years ago

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Debt

Imirrim-Chæma-Thiridion had answered a distress call. It had probably been stupid on xir part, but what was done was done.

A small ship, even smaller than xir, had crashed on a barren but breathable-to-most-species moon in the system of Hyaldnar. Xe had been making a delivery for xir mentor when xir communication system picked it up, and since xe was barely past adolescence, the journey of not even five rotations was making xem bored and seeing a crash site would be exciting. After all, it was probably an automated distress call, nothing could survive a crash to a rocky moon.

But there xe was, standing in front of a crumpled and burned wreck and the very much alive creature that had crawled out of it after perceiving xir pod landing. Imirrim cursed xir rotten luck, now xe would have to help the poor thing. Xe had been planning on just sight-seeing the wreck a bit, maybe later contact whatever species it had belonged to to tell it had crashed, if only to look good in front of xir mentor.

After a while of the creature gawking and baring it’s teeth at Imirrim, xe recognized the species as human, the fifth longest living space-faring species. Still, xe belonged to the second longest living, and Thalmors like xemself could outlive five humans each born at the moment of the previous one’s death. What had especially stuck from xir exobiology and alien anthropology lessons was humans’ way of expressing their emotions in strange and backwards ways, and their sheer capability to holding grudges. Great.

Imirrim approached the human slowly. It was approaching xem right back, still showing it’s teeth like it was attacking, but but humans expressed their emotions backwards, so that was good, right? Besides, the human was wounded and limping, and xe could outrun it if things went bad.

“Finally someone answered my call,” the human -a male, xe guessed- said as Imirrim was close enough. “I’ve been here for a week and I’m running out of water.”

A week? How was he alive?

“Oh, where are my manners,” the human said and extended the less damaged of its upper limbs towards Imirrim. “I’m Thomas Warren, from the human colony on Clyzma Al Carrim, farmer by profession.”

Imirrim carefully extended a cheliped to mimic the greeting, and did xir best not to flinch when the human grabbed it and shook it. “I am Imirrim-Chæma-Thiridion from planet Skismin, apprentice to the Grand Navigator.”

“It is very nice to meet you,” Thomas said and shook xir cheliped some more before finally letting go. “You mind taking me off this rock?”

Imirrim shifted xir weight from a foot to another to a third. “Sure.”

“Great!” Thomas said and pulled his lips even further back, revealing even more teeth, more than could possibly fit comfortably into a mouth that small. “I’ll be right back.” He limped back into the small shipwreck.

Imirrim was regretting this. It wasn’t customary to help strangers, especially from other species, since there was no telling what they could do. Humans had a reputation of being unpredictable, especially when wounded. And this ‘Thomas’ was covered in wounds, some looking much too severe for anyone to possibly survive.

Thomas emerged from his wreckage, carrying something that was clearly important if he was willing to retrieve it from a wreck while severely wounded. “So, Imirrim, was it? Where are you headed?”

Imirrim led the human to xir pod and helped him climb over the threshold. “Back to Skismin. You can get better help there.” If he stayed alive that long.

“Lovely, you’re a real life saver,” Thomas chuckled. “I’ll owe you one.”

To Imirrim’s surprise -and relief- Thomas did not die during the two rotations’ travel back to Skismin. He talked xir auditory membrane off and after a while filled the pod with the faint stench of alien blood, but all things considered he wasn’t the worst passenger. Once xe had docked the pod back on Skismin and had helped Thomas and his bag of belongings (which turned out to be an assortment of small possibly decorative items, data storage devices, clothes, and even a few ordinary rocks one could get anywhere but that were apparently 'cool’) to the nearest emergency clinic, Thomas turned to xem one last time.

“If you ever find yourself in a bad spot, call me,” he said with a serious expression xe had come to recognize during their time at the small pod. “I owe you my life, just call and I’ll pay you back.”

Imirrim stared after him for a long while before turning away and heading to tell the Grand Navigator that hir delivery was received and thanked for, and to tell xir mentor about human Thomas Warren.

After xe had told hir what had passed, Imirrim asked one last question. “Master, what does it mean when a human says they 'owe their life’ to someone?”

The Grand Navigator’s age-reddened crest rose curiously. “Like you probably know, humans are known for holding grudges and for being almost insensibly loyal. While they keep in mind all wrong that has been done to them, they do not forget a good deed done to them either. 'Owing one’s life’ means you have done something to them that they regard highly of, usually the saving of a life, and that they will do anything in their power to, as they say, 'return the favor’. Did this Thomas say this to you?”

Imirrim nodded. “Right before he went with the medical staff, he said he owes me his life, and all I need to do in a time of distress is to call him and he will come.”

The Grand Navigator raised hir upper chelipeds in a sign of pride. “You have done well, my apprentice. To earn a human’s favor is a feat of great bravery and compassion. One day, you shall become a fine and daring Navigator, like the explorers before us.”

Imirrim ruffled his crest at the praise. Maybe answering the distress call wasn’t such a bad idea after all.

–

Time went by, and Imirrim progressed from an appearance to a novice and on, up the ranks, and eventually landed a spot as the head Navigator on the long trade ship Pochella, traveling at high speeds through barely charted nebulas and dangerous asteroid fields. Xe plotted courses through the densest of rock fogs and past dangerous gravitational pulls, and not once did his calculations for the course fail.

Xe had lived many more cycles, many more than a human could ever live. Imirrim had counted- xe had kept a distant eye on Thomas Warren in case xe would ever have a need for the favor he had claimed to owe xem, but the need never came. He had died fifty-seven cycles after xe had rescued him, or seventy-two years, as humans counted time, and even more time had passed after that.

Still, even after all this time xe looked back at him for courage when daily life was hard and xir spirit was down. Xe had met and worked with humans many times now and they all shared the same spirit Thomas Warren had had, but none of them had left quite the same impression on xem as Thomas, who had smiled and joked through nine rotations on broken bones and told fondly of his family and farm back on Clyzma Al Carrim.

Imirrim had plotted a course through a particularly dense asteroid cloud, a course that would save the ship a lot of time and fuel. The ship was nearly out of the cloud when the proximity alarm went off and something clamped into the ship’s hull. The computer showed xir an approximate hologram of the something. It was a smaller and armed ship attaching itself to their ship.

The Cieruna members of the crew -small, short-lived, and feathery things with nimble hands and a sensitivity to electromagnetic fields- were screaming in terror. Pirates, they yelled, we can’t shake them off, we’re all going to die. Shush, xe said, we will not die. I’ll call for help, be quiet.

Imirrim galloped to the unoccupied communication post and sent a distress message on all frequencies. “This is Imirrim-Chæma-Thiridion, head navigator of the trade ship Pochella. We are inside the Halfway asteroid cloud. And we are under attack by pirates. Please help us.” Once the message was sent xe stepped away from the console and joined the crew in listening to the magnetic creaking of their hull in the morbid silence that had followed xir call.

The ship could not move, following the already plotted course with the extra weight and bulk of the pirate ship attached to them would be suicide, and finding a new safe route out without knowing the exact dimensions of the other ship was impossible, not to mention useless against the threat. All xe could do was hope for a miracle.

And a miracle xe got. Another proximity alarm sounded, and the computer showed an image of a charging mining pod, ten times smaller than the pirate ship and at least a hundred times smaller than Pochella. Outmatched, outgunned, it rammed the pirate ship and despite being hit by their lasers and missiles, it kept on pounding it with its grappling arms and mining lasers and asteroid bombs, everything it had. And finally, when the pod was leaking air and plasma and fuel into space, the pirate ship released its hold and retreated, engines sputtering and its hull dented and battered, and flew away from Pochella and the mad mining pod to safety of the asteroids.

“What was that? What happened? The Cieruna chirred and cheeped. "It is gone! We are saved!”

Imirrim was still looking at the hologram screen. The mining pod was all but destroyed in the short but fierce fight. Someone exited it, wearing a spacesuit and carrying something, and the pod engaged it’s barely functional engines and sped away leaving a trail of debris and smoke in its wake, until it finally exploded from the damage it had sustained a safe distance away.

Imirrim stared at the hologram for a moment, and shifted xir weight from a foot to another to a third. Xe input a code to the control panel and opened a small airlock near the creature that had saved them all. Xe set off from the bridge where xe was posted and galloped through corridors and climbed down stairs, until xe arrived in front of the airlock that had already closed and the creature that had successfully boarded the ship.

“Are you Imirrim-Chæma-Thiridion?” The creature asked. Xe nodded, all the while looking the spacesuited being up and down. Four limbs, two for walking and two for holding. No tail, short neck but a neck nonetheless. No added room for fins or spikes or crests. It was a human.

The human handed their possession to xem -a lumpy bag that both felt and looked like it had rocks in it- and pulled off their helmet.

The human was ruffled and grizzled and had spark burns on his face and his eyes were serious, but he was baring his teeth in a joyous smile. He extended a hand to greet xem and Imirrim took hold of it and shook it.

“I am Stepa Warren,” the human introduced himself. “You rescued my grandfather from a shipwreck when he was young. He spoke fondly of you til his dying day. It is an honor to meet you.”

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thewul · 6 years ago

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We ought to finish with a recap of some strategical acquisitions that we’ve seen in BCS, its not all of them but they are important.

Hyster is a way into all kinds of engines for the shipping industry and one thing where we want to be both present and strong is the shipping industry, by sea, by rail and by air.

Duster is a way into the auto and small vehicles industry, its a diversification in quest for the evolution of mobility.

Pilz Automation provides us with the necessary expertise and technology to secure our operations for both passengers and freight.

Fraunhofer for its IR technology that has potential for data transmission aboard the Gunray B1000 and indeed all of the Gunray line up.

Himoinsa for its generator and back up generator technology

Comau is becoming Bombardier Robotics for our robotics needs for now and for the future

Boeing

Airbus

Boeing and Airbus are becoming Bombardier, tree of us is too much competition for what we want to achieve, so we can skip on competition that way and focus on bringing the Gunray to the market. And yes I am afraid all previous models are getting phased out for the Gunray.

So can BCS change the world, yes it can, all of the airliners that you see in the sky right now indeed by these tree different industrials are becoming things of the past, that future generations can take a look at in an aerospace museum.

We should be thankful for their services, and build upon the expertise that delivered them to the market. They played the game until the end, and then the game changed.

I remember what Gunray said once, he said that the game is what you make it and to always go first for those that are after you. And it proved to be true like the rest.

Also we have a new version of Bombardier World eBrain, it still is a work in progress but now counts many more existing entities and newly created ones.

BCS eBrain is another way to look at BCS, and I think the best copy of BCS Legacy that we can bring to the world would be a hybrid between Personal Brain and Tumblr, where Personal Brain calls web pages from Tumblr which we do dispose of as each post has its own url.

We can then further densify the whole two ways, by allowing users to make a thread out of a post and to be able to attach files to their posts as well as start discussions. And by densifying these posts themselves with hashtags that can also be queried through an url.

All of which can be repatriated to Personal Brain where our eBrain file takes the shape of a structure, it both emulates the blog and articulates it more. Makes it practical, for example we have metrified different ships.

The link to the file will be posted here shortly. It continues to be updated so keep posted on this link:

https://bra.in/2j9PRq

The newly created entities have been the following:

Bombardier LEED, Part of Bombardier Advanced Concretes Bombardier LTE, part of Bombardier NET EXVR, EX Virtual Reality, develops virtual reality applications AUDIOPAL, An audio messaging system Bombardier Boutiques, regroups Bombardier Boutiques We Believe, workgroup and conferences B5000, Troop Transport, quite large and capable at 134.4 meters Bombardier Missile Systems, part of BWS Restaurants CCL, a restauration chain The Bombodivision, youth and sports division CL Class Opera, the final name of our 600M submarine class Thunderstorm, spaceship 336M

Thank you for having followed BCS!

#the commentaries

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mohamed87sblog · 6 years ago

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90-Day Plan to Improve Muni

90-Day Plan to Improve Muni By Julie Kirschbaum

The SFMTA’s 90-Day Plan to Improve Muni is a focused and collaborative effort to implement the SFMTA Strategic Plan through “bite-sized” pieces within a 90-day period.

Centered around the SFMTA Strategic Plan, the development of the SFMTA’s Plan to Improve Muni resulted in the creation of initiatives that differed in duration and scope. The hallmark of the Plan is the near-term initiative, which are a series of “bite-sized” actions and measurable targets that would be implemented in 90-day periods. By breaking down larger goals and initiatives into smaller near-term actions, the agency is better able to deliver effective, focused, and immediate solutions to issues, while still progressing long term plans to improve transit service.

We’re at the end of our current 90-Day period and are very encouraged by the results we’re seeing. Our initiatives for this cycle focused on safety, service reliability, subway performance, LRV 4, and Chase Center service.

Emphasis on Safety

We pursued 8 actions aimed at reducing collisions while also improving safety for operators and passengers. For instance, we were able to install more visible bumpers over 800 buses—as well as add more visible poles to our 60 trolley coaches.

Service Reliability

Service reliability continues to be a challenge for a number of reasons, but we’ve taken significant steps to minimize the impacts throughout our system. We were able to grow our operator classes—meaning more operators are on vehicles and on the streets serving our customers. Small changes that we made to the 27-Bryant route involving stop removal and re-routes has drastically improved north-south connections for our 6,700 weekday riders along that route. Our team’s dedicated work on this line was even nationally recognized for our outreach efforts connecting to passengers, residents, and merchants of different cultural backgrounds, ages, and abilities. Additionally, we continue to receive and accept 40’ trolley coaches into our fleet. We’re averaging about 2 new trolley coaches a week. Another milestone we reached this 90-day cycle was accepting enough new trolley coaches to retire all of our older ETI’s, which became less reliable and past their useful life. We’re excited to announce that we met our short-term goal of 96% service delivery, and we took important steps to reduce missed trips.

LRV 4

Standing at one of our Muni Metro platforms, you’ll see more and more LRV 4s in service picking up and dropping off passengers in both directions. We’ve met the target goal of 35 LRV 4s in service—which helped boost the overall car count to 150 vehicles in service for the rail network. Today, we have more LRVs in service than we’ve ever had before. Along with correcting previous issues with our doors and couplers, we’ve also safety certified a design for additional track brakes. This new design will help keep more LRV 4s on the streets of San Francisco delivering service, instead of in a maintenance shop. Looking ahead, we plan to increase the Siemens to Breda vehicle ratio. Today, we have 67 expansion vehicles delivered with 61 ready for service. These vehicles are the real deal and we’re encouraged by the data supporting improved performance between June and September of this year.

Improving Subway Performance

During peak commute hours, our riders aren’t shy about pointing out subway delays. Our subway performing well is critical to the livelihood of thousands of daily Muni riders. Back in August, we closed the subway early for a period of two weeks to give our maintenance staff time to complete critical maintenance tasks that cannot be completed during normal business hours. The extended window gave us the opportunity to work on overhead lines, tracks, signals, and the Automated Train Control System. We were very encouraged by the amount of work we were able to perform with very little impact on the overall ridership. In fact, we’re striving to perform this critical maintenance work periodically during slower riding seasons to keep our subway in a state of good repair.

Delivering Chase Center Service

For years, our staff has been preparing and coordinating to make sure our system would be able to accommodate an influx of riders using the system to get to Chase Center. In the past three weeks alone, we provided service to 13 Chase Center events which called for additional rail and bus service, supervision, and traffic control. It’s safe to say that our agency really worked together as one—connected to serve a purpose and deliver great, sustainable, and reliable service. From Parking Control Officers to LRV Operators to Communications Ambassadors, our agency came together operationalizing and implementing what was no doubt a monumental task. Going forward, we will continue to fine-tune and equitably balance service across the network. We’ve learned a lot so far—next up: the first Warriors pre-season game on October 5th!

Our next 90-Day Action Plan is scheduled to start on November 1, 2019. To watch our presentation on the current cycle to our Board of Directors, go to sfgovtv.org.

Published October 01, 2019 at 11:33PM https://ift.tt/2nsDs0O from Blogger https://ift.tt/2ntHKoI via saadsaytech

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the2travel · 8 years ago

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* World Travel Tips : More Biometric Scanning Is Coming Soon To U.S. Airports

Travel Tips -

To many travelers, airport security is already invasive enough. But things will get even more intense soon if Donald Trump has his way.

In both his original and revised executive orders on travel, the president called for quicker work on biometric exit, a program that aims to better verify international travelers’ identities by collecting data like fingerprints, face scans and eye scans as they leave the country. Ramped-up data collection like this is already happening in some U.S. airports, and will appear in more locations next month.

Airports have been collecting biometric data on most non-U.S. citizens for years by taking photos at Passport Control when they enter the country and checking them against government databases, Jennifer Gabris, a Customs and Border Protection spokeswoman, told HuffPost.

The catch is there’s no photo taken when travelers leave, and not all visa holders turn in the required departure form. Proponents of biometric exit say that without a way to further verify which travelers have left the U.S., it becomes hard to know who’s overstayed their visa, track potential terrorists or get accurate immigration counts. As The Hill explains:

In most cases, our federal government simply depends on good faith compliance by nonimmigrants (usually tourists, business travelers, and guest workers) to ensure that individuals honor the terms of their admission and turn in their departure form. Since an estimated 40-50 percent of unlawfully present foreign citizens (or 4.5-6 million) entered the United States legally and failed to leave the country when required, it is clear that operating on good faith is not the best way to ensure the integrity of our immigration system.

So the government is looking for a way ― probably using facial recognition, but potentially using eye scans or other measures too ― to verify which travelers have left the country by collecting biometric data right before passengers board a flight. This isn’t a new idea: Many countries already use face scans extensively in their airports and train stations, and the U.S. has been working on its own way to track exiting travelers for more than 20 years. However, CBP is now under extra pressure to choose a method and get a system into airports, said Theresa Cardinal Brown, an immigration expert at the Bipartisan Policy Center.

So yes, more face scans are coming soon, even for U.S. citizens.

In 2015, CBP started piloting biometric exit programs in America’s 10 busiest airports by using fingerprint scans. But the agency chose facial recognition as one of the easiest ways to do so, Gabris said, and will move forward with that.

Last year, CBP started piloting face-scanning technology on some travelers exiting Hartsfield–Jackson Atlanta International Airport. Pilot programs will be added to seven more airports in June, though the exact locations can’t be disclosed yet, Gabris said.

CBP also started piloting facial recognition for travelers entering the country through Washington Dulles International Airport and JFK International Airport in 2015 and 2016, respectively. Instead of the typical photo record taken at entry, these facial recognition systems compare travelers’ photos to those on their passports.

These pilot programs also scan the faces of U.S. citizens, but Gabris said that once their citizenship is confirmed, their data is deleted, while non-citizens’ data is kept on file. She said the same will be true of whatever biometric exit system becomes permanent.

This push didn’t start with Donald Trump, but he wants it to happen soon.

Though the president’s now-infamous travel ban aims to “expedite the completion and implementation” of biometric tracking, the program didn’t originate with Trump’s borders-focused administration.

Bill Clinton’s 1996 immigration act called for an automated entry-exit system to track travelers, and later bills named biometrics as a way to do so, Brown said. Progress continued off-and-on during subsequent administrations and has been moving more quickly since 2013, when CBP was officially put in charge of the biometric exit project.

There’s some concern, however, that Trump’s advisors will disregard previous work on the project, failing to examine how their collection of personal data jives with U.S. privacy law, said John Cohen, former counterterrorism coordinator at the Department of Homeland Security.

Groups like the American Civil Liberties Union have called biometric data collection a threat to privacy. What’s more, U.S. facial recognition systems have higher rates of error in recognizing minorities, because much of the technology was developed using Caucasian faces in testing. Using it in airports could increase racial profiling of passengers, said Rich Stolz, executive director of OneAmerica, a civil rights group that advocates for immigrants.

“We’ve seen evidence that [facial recognition] can be particularly inaccurate in dealing with minority populations, or people who don’t look white,” he said. Using it “wouldn’t address serious concerns about the frequency with which minorities get pulled aside for second look.”

In Cohen’s opinion, the Trump administration would be wise to address concerns like these.

“The current administration is still in a learning curve about these issues,” he said. “I believe the attitude in the White House is they’re resistant to talk with individuals outside their circle who have been involved with security over the last few years... Hopefully they’ll reach out to those experts.”

It’ll be a while before face scanners are in every airport, if they make it to every airport at all.

Making facial recognition the official technology for biometric exit will be expensive, said Cohen. In order for the system to work to its full capacity, CBP will have to install face-scanning cameras in every airport, land border and seaport in the country.

Finding a way to take exit photos without causing travel delays will cost even more.

“[CBP] wants passive technology that can grab data as people walk by,” Brown said. “The most efficient way is literally on the jetway, as people are boarding a plane... But we’ve never built airports to do that.”

Cohen said he thinks U.S. airports can make better use of the information they already collect ― like entry photos and forms ― to achieve the same goals as a biometric exit program that uses facial recognition, he said. To him, a complete overhaul isn’t necessary, never mind feasible.

Indeed, said Gabris, “there are many more infrastructure and process challenges that exist for biometric exit.”

-- This feed and its contents are the property of The Huffington Post, and use is subject to our terms. It may be used for personal consumption, but may not be distributed on a website.

World Travel Tips : Find cheap flights, hotels and car rentals. Plan your trip with travel guides, personalized recommendations, articles, deals and more. When you travel, you want your bags to travel with you. Follow these tips from travel professionals on how not to lose your luggage.

#best travel guides #Travel Tips #Travel Information #Travel Guide #Travel Agent News for The travel

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david8381-blog · 8 years ago

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Predictive Analytics Market Survey, Key players, Share, Size and forecast to 2020

Industry Insight

Increasing demand for accurate forecasting in business activities is the key driver for predictive analytics market. Predictive analytics is the activity of data mining which deals with extracting important data from given database, used to analyse the trends and behaviour patterns to predict the future. It is also used to forecast the results. Predictive analysis relies on defining relationship between different variables behaviour from past occurrence and exploit them to predict the future outcome.

Database management, forecasting, data warehouses, data mining, CRM analytics, smart, logistics, decision making process, data visualization in dashboards and increasing demand of business having analytic capabilities are expected to drive the predictive analytics technology in coming six years. However, traditional measures, technological incapability and cost of developing predictive analytics software are anticipated to challenge the market growth over the forecast period. Increasing demand for more than a point solution is expected to offer the opportunity for the growth of predictive analytics market in near future.

Application Insight

Banking, financial service & insurance (BFSI) has impact of predictive analytics on processes of loan, insurance, financial activities and fulfilment of financial needs which is going to impact the predictive analytics market positively. Environment segment uses predictive analytics for weather forecast, natural calamities forecast, flights safety among others. In government segment, predictive analytics decreases waste, fraud and abuse, maximizes productivity of agency personnel, drives smarter decisions within government agencies and automates manual processes which are expected to expel the growth of the market. Healthcare segment utilizes predictive analytics in chronic disease management, patient care, hospital administration and supply chain efficiencies, which are expected to drive the market growth in coming years.

In industries and retail business, predictive analytics helps to define a view of customers by analyzing the wealth of data within the organization. Retail business is expected to witness the highest growth over the forecast period. Sports segment uses predictive analysis for player-tracking systems to understand how individual players move through every passage of play and improve performance which is going to impact the market growth positively. Transportation is made advanced by using predictive analytics activities such as sensors in passenger counting, vehicle locator systems, ticketing and fare collection systems. Telecom industry uses predictive analytics in departments such as marketing, sales and CRM by implementing churn, cross-sell and up-sell and pricing optimization. Transportation and telecom industries are expected to witness the fastest growth in near future.

Browse Details of Report @ https://www.hexaresearch.com/upcoming-research/predictive-analytics-market

Service Type

The predictive analytics facilitates to solve the increased awareness of fraud. Predictive analytics deals with emails, chat messages, phone records and other structured and unstructured data which enables security and lessen the chances of fraud. These factors are expected to impact the growth of the market positively. In marketing, predictive analytics is used to lift the sales from previous year by accurate forecasting and companies adopt best practices associated with developing and using data-driven customer insights. The decisions are taken based on the analysis of behavioral data.

These activities are going to expel the market growth over the forecast period. Predictive operational analytics helps to represent actions and counter actions taken to manage and improve performance and to get operations back on track if something has gone awry. These operational activities enhances the efficiency in retail sector with the help of predictive analytics and are anticipated as the major factors to drive the market in coming years. Predictive analytics solves risk problem connected to any decision in business owing to the precised decision taken by data analytics and going to drive the market growth.

Regional Insight

North America has the largest market share in the predictive analytics market due to massive amount of data deluge and entrance in multiple domains. Its applications are largely towards manufacturing, healthcare, transportation, logistics, mobile device and broadband technology domains in North America. In Asia pacific, the countries including China, Japan, India, and Australia are expected to witness an increase in the adoption rate of predictive analytics over the forecast period. Middle East and rest of the world is expected to witness growth in similar line.

Competitive Insight

Providers of predictive analytics technology includes SAS predictive analytics, IBM, Revolution Analytics, Oracle, Statsoft, FICO, Salford Systems, TIBCO, Oracle Advanced Analytics RapidMiner, GraphLab Create, KXEN, STATISTICA, TIMi Suite, Pervasive, Portrait, Predixion, Data Science Studio, Angoss predictive analytics, H2O, Analytics solver, Viscovery Data Mining Suite, Mathematica, Minitab, MATLAB and SAP InfiniteInsight.. IBM offers ensuring the data being analyzed is safe, secure and accurate, predictive analytics software to make data-based decisions and the task of handling all types of data and analytics. Oracle is one of the biggest players in predictive analytics market providing software for database management, data ware housing, data integration, database security and big data appliance.

Browse Related Category Market Reports @ https://www.hexaresearch.com/research-category/next-generation-technologies-industry

About Us:

Hexa Research is a market research and consulting organization, offering industry reports, custom research and consulting services to a host of key industries across the globe. We offer comprehensive business intelligence in the form of industry reports which help our clients obtain clarity about their business environment and enable them to undertake strategic growth initiatives.

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mohamed87sblog · 6 years ago

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90-Day Plan to Improve Muni

90-Day Plan to Improve Muni By Julie Kirschbaum

The SFMTA’s 90-Day Plan to Improve Muni is a focused and collaborative effort to implement the SFMTA Strategic Plan through “bite-sized” pieces within a 90-day period.

Emphasis on Safety

Service Reliability

LRV 4

Improving Subway Performance

Delivering Chase Center Service

Our next 90-Day Action Plan is scheduled to start on November 1, 2019. To watch our presentation on the current cycle to our Board of Directors, go to sfgovtv.org.

Published October 01, 2019 at 11:33PM https://ift.tt/2nsDs0O IFTTT, SFMTA from Blogger https://ift.tt/2ntHKoI via https://www.facebook.com/saadsaytech/

#IFTTT #SFMTA

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