Artificial intelligence systems are bridging the gap between real world and the digital world. AI and Machine Learning systems are performing the tasks that are considered important as well as more difficult. One such application of artificial intelligence is the automatic number plate.
The License Plate Recognition System is based on the concept of optical character recognition to identify the number written on the number plate. Or, we can say that LPR takes an image of the vehicle as the input and outputs the number written on the number plate.
Efficiency and improved energy measures begins with understanding where your energy is used, or misused. Deep metering, DOE modeling, and analysis are a SaaS solution that quickly identify outliers and help measure the impact of your work.
We lower the cost of operating a building through providing deep analytics, and then diagnosing issues so you can act. From data-driven project work to smart monitored commissioning based on deep analytics, our services help your teams work better.
What comes after understanding energy use, acting upon insights, and operating with zero drift? Predictive control. Our services take buildings to the next level with autonomous, continuous efficiency. It's AI that optimizes your energy efficiency and building operations, everyday, 24/7, automatically.
At present, maintenance is often preventive, time-based rather than based on actual equipment conditions and predictive methods. Maintenance on each asset is performed at more frequent, regular intervals to lessen the likelihood of costly failures. This results in unnecessary maintenance costs and causes unanticipated downtime.
Predictive Maintenance (PdM) is a maintenance technique, based on the monitoring of equipment conditions combined with different sets of (real-time) analytics to achieve cost savings.
Optimize your maintenance strategy with our data-driven action plans. Calculate your asset risk and assess the criticality of failure based on the world’s largest database of industrial logic.
Determine why, where and how your assets might fail using root-cause analysis, failure mode and effects analysis, and historical work order data.
Monitor all of your assets — whether they’re connected with sensors or unconnected and unsensored — to make the best maintenance decision for your business.
Get data-driven recommendations based on real-time asset conditions plus historical asset data, fluids and inspection data, fault codes, and operating thresholds.
Unlock new operational efficiencies by making proactive maintenance decisions based on predictive insights.
Our industrial AI and machine learning engines detect asset anomalies and help predict and prevent problems before they happen. Leverage asset-centric and fleet-wide visualizations to understand how you can drive financial outcomes that impact your business.
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