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Internet of Things (IoT) devices are rapidly expanding in many areas,including deep mines, space, industrial environments, and health monitoringsystems. Most of the sensors and actuators are battery-powered, and thesebatteries have a finite lifespan. Maintaining and replacing these manybatteries increases the maintenance cost of IoT systems and causes massiveenvironmental damage. Energy-harvesting devices (EHDs) are the alternative andpromising solution for these battery-operated IoT devices. These EHDs collectenergy from the environment and use it for daily computations, like collectingand processing data from the sensors and actuators. Using EHDs in IoT reducesoverall maintenance costs and makes the IoT system energy-sufficient. However,energy availability from these EHDs is unpredictable, resulting in frequentpower failures.  Most of these devices use volatile memories as storage elements, implyingthat all collected data and decisions made by the IoT devices are lost duringfrequent power failures, resulting in two possible overheads. First, the IoTdevice must execute the application from the beginning whenever power comesback. Second, IoT devices may make wrong decisions by considering incompletedata, i.e., data-inconsistency issues. To address these two challenges, acomputing model is required that backs up the collected data during powerfailures and restores it for later computations; this type of computing isdefined as intermittent computing. However, this computing model doesn't workwith conventional processors or memories. Non-volatile memory and processorsare required to design a battery-less IoT device that supports intermittentcomputing.

Design of Energy Harvesting based Hardware for IoT Applications