We present radio-frequency (RF) information harvesting, a chan-nel sensing technique that takes advantage of the energy in the wireless medium to detect channel activity at essentially no en-ergy cost. RF information harvesting is essential for event-driven wireless sensing applications using battery-less devices that har-vest tiny amounts of energy from impromptu events, such as op-erating a switch, and then transmit the event notification to a one-hop gateway. As multiple such devices may concurrently de-tect events, coordinating access to the channel is key. RF infor-mation harvesting allows devices to break the symmetry between concurrently-transmitting devices based on the harvested energy from the ongoing transmissions. To demonstrate the benefits of RF information harvesting, we integrate it in a tailor-made ultra low-power hardware MAC protocol we call Radio Frequency-Distance Packet Queuing (RF-DiPaQ). We build a hardware/software proto-type of RF-DiPaQ and use an established Markov framework to study its performance at scale. Comparing RF-DiPaQ against sta-ple contention-based MAC protocols, we show that it outperforms pure Aloha and 1-CSMA by factors of 3.55 and 1.21 respectively in throughput, while it saturates at more than double the offered load compared to 1-CSMA. As traffic increases, the energy saving of RF-DiPaQ against CSMA protocols increases, consuming 36% less energy than np-CSMA at typical offered loads.

Internet of Things (IoT) has created a niche in the last decade. We are in the midst of an unprecedented growth of automation and smart systems, driven by the miniaturization of sensing and computing & communication technologies. Even though battery technology has grown to a large extent, it is still not possible to power these sensors for long, especially in situations where sensors need to provide data at a higher frequency, which drains the batteries fast. Thus, recently researchers are looking into various means of self-powered sensing systems that harvest energy from the ambiance. In this paper, we characterize and optimize a piezoelectric energy harvesting device consisting of a cantilever beam, which is suitable for self-powered Wireless Sensor Network (WSN) nodes in the rail transport networks. The integrated unimorph-piezoelectric sensor harvests energy from ambient vibration. We attune the harvester parameters to the low range of ambient vibration frequencies and demonstrate an experimental model to validate the results of our setup. Vibration frequency and amplitude are measured by performing real experiments inside trains on the routes of the Dutch and German railway network. Each harvester provides 0.72µJ to 0.19mJ per hour depending on the vibration. Multiple of them can be utilized as secondary energy sources inside trains to measure the ambient vibration while harvesting to make it a perpetually powered sensor