Historically, battery is the power source for mobile, embedded and remote system applications. However, the development of battery techniques does not follow the Moore's Law. The large physical size, limited electric quantity and high-cost replacement process always restrict the performance of the application such as embedded systems, wireless sensors networks and lower-power electronics. Energy harvesting, a technique which enables the applications to scavenge energy from RF signal from TV towers, solar energy, piezoelectric driven by motion of people and thermal energy from the temperature difference, which could dramatically extend the operating lifetime of applications. Thus, energy harvesting is important for the sustainable operations of an application.
Piezoelectric energy harvesting from bridge vibrations has attracted many researchers not because it provides a clean and autonomous solution to power portable electronic devices, in addition, it helps in making a smart city. This paper focuses on energy harvesting from low-frequency bridge vibrations which includes vibrations measurements from a city flyover and laboratory experiment using traditional rectifier circuit at low frequency and small amplitude vibrations for storage. The typical practical issues have been addressed associated with PEH from bridge vibrations and electrical circuitry. In this paper, we present a software control method that maximizes the sensing rate of wireless sensor networks (WSN) that are solely powered by ambient RF power. Different from all other energy harvesting WSN systems, RF powered systems present a new challenge for the energy management. A WSN node repeatedly charges and discharges at short intervals depending on the energy intake. A capacitor is used for an energy storage in the energy harvesting system because of its efficient charge and discharge performance and infinite recharge cycles. When this charging time is too short, the node is more likely to experience an energy shortage. On the contrary, if it is too long, more energy is lost because of the leakage in the capacitor. Therefore, we implemented an adaptive duty cycle control scheme that is optimized for RF energy harvesting. This method maximizes the sensing rate considering the leakage problem, a factor that has never previously been studied in this context. Our control scheme improves efficiency by aggregate evaluation of the operation reliability and leakage reduction. Wearable health sensors are about to change our health system. While several technological improvements have been presented to enhance performance and energy-efficiency, battery runtime is still a critical concern for practical use of wearable biomedical sensor systems. The runtime limitation is directly related to the battery size, which is another concern regarding practicality and customer acceptance. We introduced ULPSEK—Ultra-Low-Power Sensor Evaluation Kit—for evaluation of biomedical sensors and monitoring applications ( http: ulpsek.com ). ULPSEK includes a multiparameter sensor measuring and processing electrocardiogram, respiration, motion, body temperature, and photoplethysmography. Instead of a battery, ULPSEK is powered using an efficient body heat harvester. The harvester produced 171 @math W on average, which was sufficient to power the sensor below 25 @math C ambient temperature. We present design issues regarding the power supply and the power distribution network of the ULPSEK sensor platform. Due to the security aspect of self-powered health sensors, we suggest a hybrid solution consisting of a battery charged by a harvester.