in: Wireless Automation as an Enabler for the Next Industrial Revolution, Muhammad Ali Imran,Sajjad Hussain,Qammer H. Abbasi, Editor, John Wiley & Sons, West Sussex, UK , London, pp.19-45, 2019
This chapter focuses on state‐of‐the‐art life‐span extension methods for wireless sensor networks (WSNs) with high‐level taxonomy: energy harvesting and energy conservation. WSNs render the industrial processes more dynamic and agile owing to their real‐time monitoring capabilities, hence reducing the operational expenditure with minimal installation cost. However, the life‐span of WSNs should be as long as possible in order for the industry to capitalize on the offered gain and maximize their cost effectiveness. Energy consumption is the main determinant factor for the life‐span of WSNs, since the sensor nodes are typically energy constraint devices due to their limited batteries. The chapter introduces WSNs in general, and focuses on Industrial WSNs by presenting their distinctive characteristics and some selected applications. Lastly, it demonstrates Q learning assisted energy efficient model, and provides the simulation results revealing that it is capable of improving the application specific gains of the WSN while reducing the energy consumption.