The worlds of artificial intelligence and the internet of things almost invariably overlap, and almost nowhere is this more obvious to the consumer than in the products of People Power, who has just unveiled its latest Pro Energy 2.0 platform. The new platform is an improvement over the firm’s existing product and is essentially designed to “learn” consumers’ behaviors in regards to energy use, and help them optimize their usage for comfort, convenience, and energy savings. It can not only sense and correct inefficient usage due to human error but can also figure out when something is wrong and an energy audit may be needed, such as with a house whose poor insulation makes turning the air conditioning off for a few minutes in the summer an uncomfortable proposition.
Pro Energy 2.0’s primary component is Maestro 2.0, which includes, among other things, a Demand Response Management System. Essentially, this system is able to utilize built-in AI components to monitor a customer’s account, activities, and devices, and figure out how best to manage it all based on an AI program provided by People Power. It’s capable of managing large-scale enterprise-level deployments, as well as managing and monitoring individual customer’s home using both per-home data and aggregated trend insights. It can also take the weather into account in figuring out the current efficiency level of a given deployment. This can help it to detect inefficiencies that may require an energy audit. It can even monitor lighting usage to help optimize for energy saving, and automatically mimic normal usage while a customer is gone in order to deter possible burglary.
The platform is not directly consumer-facing; its components, called microservices, are meant to be delivered through energy providers, though both consumers and energy providers are welcome to contact People Power to order, pay for, and get help with the services. Regardless of whether an energy provider or consumer is in charge of the account with People Power, new microservices can be added to an implementation at any time. Because the platform is based on easy-to-insert IoT equipment and is deliverable over existing connections, even microservices that depend on some new hardware can be added or removed relatively quickly.