SpotDy BigAI for Energy

Cutting fuel usage and achieving efficient usage of energy for energy companies have become imperative with governments across world legislating tougher regulations. Studies done by various agencies and consulting companies have came to the same conclusion: saving energy and fuel efficiency are best achieved with installation of new smart devices that collect more data on energy usage and inter connection of those devices that communicate among themselves.

What SpotDy can do for Energy?

Smart device software stack

SpotDy can provide energy companies in helping design smart devices, process the data generated through those devices, and using machine learning analytics to exactly pinpoint sources of energy usage inefficiencies.

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Interconnected devices

Interconnected devices and IoT is the future. SpotDy has the infrastructure to support collection of data from various devices and process the data on real time to get a holistic view of energy usage, thereby saving fuel and achieving energy usage efficiency.

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Use Case

A local metro government is committed to preserve the diversity while building a more equitable community where all citizens have a chance to succeed and nobody gets left behind in its latest strategy document.

A Dallas based energy company wants to price electricity usage dynamically and eliminate the need for creating additional generating capacity to meet the peak demand. The company took advantage of big data analytics and IoT technology, and installed smart meters that read electricity usage on real time. This eliminated the need to send someone for reading the meter once a month, and the company can now read the electricity usage remotely once every fifteen minutes. Using real time data, the company priced electricity usage differently for peak and off-peak hours. The company even promoted ?Do your laundry or run the dishwasher at night, and pay nothing for your Energy Charges?, which was very successful in getting new customers.

Moreover, by having a dynamically changing demand curve, the company eliminates the need for creating additional generating capacity to meet peak demand, The energy company used big data analytics to reshape energy usage and gained revenues from new customers and saved millions of dollars worth of investment in generating capacity and plant maintenance costs.

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