This article gives a summary of the IEEE P1918.1 working group's standardization results.

Abstract-Miniaturization of devices with higher computational capacity coupled with advancement in communication technologies is driving the growth of deployment of sensors and actuators in our surroundings. To keep up the pace with this growth, these tiny, battery-powered devices need small-sized and high-energy density batteries for longer operation time, which calls for improvement in battery technologies. An alternative is to harvest energy from the environment. An important aspect of energy harvesting is that the devices go through birth and death cycle with respect to their power unlike battery powered ones. Another important aspect is that context information is also generated while devices harvest energy from their ambiance. In this article we provide a comprehensive study of various types of energy harvesting techniques. We then provide some models used in energy harvesting systems and the design of such systems. We also throw light on the power management and networking aspects of the energy harvesting devices. At the end we discuss the major issues and avenues for further research.

Long-range wide-area network (LoRaWAN) is an energy-efficient and inexpensive networking technology that is rapidly being adopted for many Internet-of-Things applications. In this study, we perform extensive measurements on a new LoRaWAN deployment to characterise the spatio-temporal properties of the LoRaWAN channel. Our experiments reveal that LoRaWAN frames are mostly lost due to the channel effects, which are adverse when the end-devices are mobile. The frame losses are up to 70 percent, which can be bursty for both mobile and stationary scenarios. Frame losses result in data losses since the frames are transmitted only once in the basic configuration. To reduce data losses in LoRaWAN, we design a novel coding scheme for data recovery called DaRe that works on the application layer. DaRe combines techniques from convolutional and fountain codes. By implementing DaRe, we show that 99 percent of the data can be recovered with a code rate of 1/2 when the frame loss is up to 40 percent. Compared to the repetition coding scheme, DaRe provides 21 percent higher data recovery and can save up to 42 percent of the energy consumed on a transmission for 10-byte data units. We also show that DaRe provides better resilience to bursty frame losses.

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