Tag Archives: Smart Energy

Wireless sensor network developers are finding an expanding ecosystem with Internet of Things markets, according to a recent survey by global technology research firm ON World.

In collaboration with several industry alliances, ON World recently completed a survey with leading WSN equipment/device manufacturers, service providers, software developers, systems integrators, component suppliers and end users.

Participants include members of the Bluetooth SIG, CABA, Continua Health Alliance, EnOcean Alliance, IPSO Alliance, ZigBee Alliance and Z-Wave Alliance.

A few of the key findings were:

  • The smart home is currently targeted by nearly two thirds of the respondents.
  • Energy management and lighting are the most commonly targeted current WSN application areas.
  • 43% are planning WSN solutions for health and fitness
  • Likely high growth markets include personal / lifestyle sensors, home and building controls, and smart city applications such as traffic sensing and parking management.
  • Nearly half of the respondents are using ZigBee followed by WiFi, 6LoWPAN and Bluetooth Low Energy (Bluetooth Smart).
  • Data reliability, equipment costs and battery lifetime are the top three most important WSN adoption considerations.
  • Energy harvesting is ranked as one of the top five most important WSN innovation areas and 40% of the respondents have at least tested energy harvesting.

AutoGrid pulls in $9M to turn ‘big data’ into an energy source

The San Francisco Bay Area based AutoGrid, a startup founded in 2011, pulled in $9 million to continue the development of its software that helps utilities and businesses control their energy usage.

Founder and chief executive, Dr. Amit Narayan stated that “The capacity of the [smart] grid is not deployed efficiently”. His technology analyzes data collected by smart meters (by putting sensors on the electric grid) to enable operators to meet supply and demand. With the use of machine learning, which gets smarter over time, it can make predictions about energy consumption patterns inside buildings and across service regions. It can then forecast how much electricity will potentially be needed in the upcoming hours or days.

With the advent of analytics tools, we can begin to make predictions about the future and further optimize energy usage. “Up to 20 percent of the power-generating assets in some regions only get deployed ten or fewer days a year,” said Dr. Narayan. His current major customers include the City of Palo Alto Utilities and Sacramento Municipal Utility District.

  Dr. Amit Narayan

Before AutoGrid, Dr Amit Narayan taught on the topic of electronic design automation software at Berkeley and Stanford. He founded Berkeley Design Automation, which is used by more than 20 of the top 25 chip developers.

What’s interesting from a competitive standpoint is the company’s focus on pattern-recognition and predictive analysis. The company’s investors include Foundation Capital,  Voyager Capital, and Stanford University. Last year, it won a $5 million grant from the U.S. Department of Energy program to devote to improving the product.

Smart meters, it’s the future!