The Sensors & Instrumentation Knowledge Transfer Network
(KTN) based in London, UK, has published an study titled “Power Management Technologies to Enable Remote and Wireless Sensing” which main focus is on establishing best practices and identifying remaining performance barriers in implementing self-powered wireless sensor networks.
The methodologies have been grouped in 3 sets depending on the level the optimization focuses on. Issues explored related to the themes of:
- Microprocessor level Power Management
- Node level Power Management
- Network-level Power Management
One of the success cases the study points out is the energy saving modes of the Waspmote platform. The usage of three different sleep modes: sleep, deep sleep and hibernate, the last one being the lowest consuming mode of all the market mote platforms (0.7uA) reinforces the idea of Waspmote as the best option in order to create long life self powered sensor networks.
