The increasing demand for energy conservation and the emergence of the Internet-of-Things have presented new opportunities for home energy management (HEM) systems and devices on the market, where they are being used to curtail and improve the energy consumption and production profile of a dwelling on behalf of a consumer.
WeSmart, a HEM system solution provider based out of Shanghai, believes that households are becoming more and more aware of the impact energy consumption have on their budget, and most notably, on the environment.
“The home market is our next target. Today, we are deploying our platform solution with tech-savvy users, who already know about IoT sensors and want to try them at home,” WeSmart CEO François Bordes said.
“One of the main benefits of WeSmart is to bring a real-time information about energy consumption but also air quality, bringing all that information on a single dashboard.”
According to Bordes, the WeSmart software platform goes far beyond monitoring electricity consumption, as it combines data from an unlimited number of IoT sensors that track intelligently electricity, water use, temperature, motion, and air quality. The data collected are fed through analytic algorithms, which then display results on a user-friendly dashboard available online or via mobile devices.
Meanwhile, compared with HEM solutions for the B2B market, “the home market should use very simple interfaces and easy connectivity. Individuals don't want to spend a lot of time understanding their energy consumption, they want a clear, sharp information that is automatically available,” he explained.
Commenting on how WeSmart manages to stay unique amongst the plethora of solutions currently on offer by other HEM providers, the company executive believes that it all boils down to simplicity. “Now the winning offerings will be the one who really offer a great user experience, simplicity and instantaneous information.”
But as easy as it may sound, Bordes however said that visualization and control will not be a sustainable solution for future HEM users.
“In order to provide a really useful information, we need to work on machine learning that will help make our app really 'think' as humans,” he concluded.