| dc.description.abstract | This thesis presents a comprehensive investigation into the development of energy-efficient, low-cost wireless sensor systems in the context of the Internet of Things landscape. We examined two sensor technologies, microwave sensor systems and conventional commercial sensors. The former is a novel technology, in which the microwave components in a wireless transceiver are equipped with sensing capabilities. On the other hand, our exploration of conventional sensors focuses on passive analog sensors modeled as variable capacitors.
In understanding the behavior of sensor components, we dive deep into spectral lines analysis, focusing on multi-tone and single-tone parameter estimation. This theoretical foundation allows us to identify and improve the complexity and accuracy of the processes in the sensor system.
For sensor system design, we consider two main strategies: Redundancy mitigation, and power-intensive task relocation. Drawing from our theoretical insights, we propose designs for both technologies. Each proposed design prioritizes cost and energy efficiency in the integration of sensors with wireless transceivers while adhering to the communication standards. For the microwave sensors, our design supports using commercial wireless transceivers, since the modification is restricted to the tail-end of the radio frequency chain. Alternatively, in our second design, we suggest the integration of conventional sensors with a radio frequency identification system, emphasizing its inherent cost and energy efficiencies.
We validate our designs by formal analysis, simulations, and in the case of microwave sensing, empirical tests. Contrasting with the state-of-the-art solutions, the proposed designs stand out for their energy efficiency, costeffectiveness, accuracy, and reduced measurement time. This research not only meets its intended research objectives but also lays a robust groundwork for future efforts in joint communication and sensing signal processing. | en_US |
