#Forecasting energy generation with microsoft fabric and machine learning

[acuvate-updates]

Optimizing Water Usage: Predicting Irrigation Needs with Microsoft Fabric and Machine Learning

Understanding the Challenge Managing agricultural water usage is complex. Farmers must consider weather changes, soil conditions, and crop types, yet often rely on manual estimates. We wanted to help predict irrigation needs in advance, making farming more efficient and sustainable.

Why We Built This Our goal was to support farmers in planning water use more precisely, reduce waste, and improve crop health. We aimed to use data they already had — soil moisture readings, weather forecasts, and irrigation logs — and integrate predictions into simple, accessible tools.

Our Solution Data from soil sensors and weather APIs is ingested into Microsoft Fabric. Using Dataflows, we clean and prepare this data, storing it in OneLake for easy access. We trained a time-series LSTM model to forecast water requirements for the next five days, continuously updating with new data.

The model is deployed via Azure ML and integrated into a PowerApps dashboard so farmers can view daily water recommendations easily.

LSTM was chosen for its ability to understand patterns over time, such as the delayed impact of rainfall or gradual soil moisture depletion.

System Architecture

Data Acquisition: Soil moisture sensors, local weather data, and irrigation records.

Data Storage: Centralized in OneLake within Microsoft Fabric.

Model Training: Historical and live data processed and used to train LSTM models via Fabric’s ML capabilities.

Model Deployment: Managed and deployed through Azure ML with endpoints for real-time use.

Prediction Output: Recommendations displayed through PowerApps, allowing quick on-field decisions.

What Worked Well Microsoft Fabric simplified data integration and transformation, while PowerApps allowed easy sharing of results without new training for farmers.

Challenges We faced difficulties with inconsistent sensor data, syncing different data sources, and tuning the model to avoid over- or under-watering suggestions.

Why This Approach Worked The focus was on practicality and ease of use rather than complexity. Microsoft Fabric offered strong data handling, and Azure ML made deployment straightforward, creating a reliable system for field use.

Conclusion This solution shows that impactful innovation doesn’t always mean building something new from scratch. By combining existing tools smartly, we helped farmers make informed decisions, conserve water, and improve yields.

If you want to read in detail, visit: https://acuvate.com/blog/irrigation-forecasting-with-microsoft-fabric/

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Edge Analytics Market: Investment by Several Firms to Augment the Future Scope of Growth

The global edge analytics market anticipated to experience a significant rise in coming years. So as to build up a fortification, sharp players in the worldwide edge analytics market are attempting to extend their topographical impressions through painstakingly considered mergers and acquisitions. To that end they are additionally managing an account upon vital organizations. Another prominent procedure with organizations needing to reinforce their positions is broadening of product portfolio. Players are additionally investing money cash into improvement of very compelling systematic models to allure more takers. There are several leading players in the worldwide edge analytics market are Cisco Systems, Inc., IBM Corporation, Oracle Corporation, PTC Inc., SAS Institute, AGT International, Inc., General Electric, Microsoft Corporation, , Greenwave Systems, and SAP SE.

Browse Premium Industry Research Report with Analysis: https://www.transparencymarketresearch.com/edge-analytics-market.html

According to a recent report by Transparency Market Research (TMR), edge analytics market is foreseen to project a strong growth with a noticeable CAGR of 27.6% within the forecast period. Moreover, the entire market value is evaluated to be around US$ 25.569 bn by the end of year 2025. In view of industry vertical, the manufacturing fragment, is anticipated to hold a market offer of 16.4% for the worldwide edge analytics market in 2025. This is a result of the rise of industry 4.0 idea, in which mechanization and information trade are utilized as a part of assembling innovations through digital physical frameworks, the IoT, cognitive computing, and cloud computing.

Increased in Data Generation and Management to Fuel the Market Growth

As per an analyst in TMR, on a bleeding edge of driving development in the worldwide edge analytics market is the Internet of Things (IoT). The enormous measures of information produced by them have to be examined for noteworthy bits of knowledge by associations. Exchanging such essential information from their place of beginning, which can be remote areas, by means of web or Bluetooth, to cloud server farms for investigation can be unsafe and moderate. This thus can influence an association's legitimate working.

The rising utilization of IoT in shrewd urban areas, brilliant assembling, oil and penetrating, and so on has positively affected the worldwide edge analytics market up until now. In the years ahead as well, these portions will probably support the market. Truth be told, many organizations in the edge analytics area are doing vital coordinated efforts to help fabricating with the edge analytics. This has helped the market.

Get PDF Brochure for more Professional & Technical industry insights: https://www.transparencymarketresearch.com/sample/sample.php?flag=B&rep_id=29966

Proliferation of IoT to Boost up the Market Demand

Asia Pacific is another key area, which is anticipated to represent most extreme development – a CAGR of 28.5% in the estimate time frame. This is a direct result of the considerable interest being developed of savvy urban communities which utilizes Internet of Things (IoT) to assemble vital information. Likewise, it additionally empowers precise and quick basic leadership in basic circumstances, for example, crises, wrongdoing, security break, and so on. Edge analytics help companies to get further developed information speedier by applying progressed analytics and machine learning at the purpose of information gathering. What's more, it additionally supports yields, builds throughput, diminishes downtime, and enhances proficiency. The multiplication of IoT and associated gadgets is relied upon to drive the edge analytics market. Multiplication of information because of the ascent of web of thing (IoT) all inclusive, and expanded dangers to the undertaking system, for example, digital assaults and other security breaks are a portion of the reasons which are required to drive the edge analytics market all around.

The study presented here is based on a report by Transparency Market Research (TMR), titled, “Edge Analytics Market (Deployment Type - On-premise and Cloud; Industry Vertical - Retail, Healthcare, BFSI, Oil and Gas, Transportation and Logistics, Manufacturing, Government and Defense, and Energy) - Global Industry Analysis, Size, Share, Growth, Trends, and Forecast 2017 - 2025.”