The more technology advances, the extra benefits to the public and devices that connect to the internet have increased as well, commonly known as internet of things (IoT). The battery lifespan of these devices rises with technical concerns where an alternative to traditional energy attainment is needed. As the way forward, wireless sensor networks (WSNs) and IoT are tested to be used as novel energy alternatives through energy harvesting (EH). This study identifies the availability of energy by location. Similarly, it focuses on the sensor node's architecture with EH capabilities expanding to the classification of five EH techniques. It evaluates the EH developments in search of minimal resource utilization associated with WSNs. Its extensive distribution of interconnected devices is connected via the internet and other related high-tech innovations. Finally, it discusses the feasibility of energy storage and its potential for WSNs, paving the way for future trends and motivations.
TopIntroduction
WSNs have proved a notable multi-hop wireless network testing role, this is because of its potential application in conservation and operational systems for safety like using semi or autonomous drone for public control (Shafik, 2023), proper energy optimization. The architecture of communication protocols, localization, monitoring strategies, and power management are key in this paradigm. IoT-based hedge systems have demonstrated a positive for solar power generation. Prediction algorithms or models on edges availed a correlation coefficient of 0.917 and coefficient of determination value of 0.841 (Syu et al., 2021). WSNs were inspired by technological emphasis, for example, conserving natural resources and changing them into energy. The WSN nodes usually are battery-powered. The system is considered “empty” when its power is exhausted; batteries can either be replaced or recharged in minimal applications. The replacement or recharging process tends to be slow and costly and reduces network performance, but it is inevitable (Hadas et al., 2018).
EH is defined as to the conversion ambient energy present in the ecosystem into electrical energy for both natural and artificial use. There is increased device connectivity to the internet and its associated merits like increased resource sharing, improved computation speed, and reduced latency. Regarding the IoT application in reducing energy consumption, several appropriations have been highlighted within this study as core factors that need to be addressed to proper energy utilization by the intelligent systems like situation or pandemic forecasts and the public. Identified ones include industrial condition monitoring, operation isolation setups, WSNs, wireless pressure sensors, and Pipeline Actuators. Free energy also comes at a cost and going about the entire system is critical in deciding how energy harvesting can satisfy the power needs. To affect this issue, green energy, collecting, wasted energy, self-charging, consumer (customer) electronics, and drop-in battery replacement are identified as possible ways to save energy. WSNs perform computing through sound resource management owing to their pervasive existence (Syu et al., 2021). Energy mainly entails three main chains from the supply to transformation to consumption as Figure 1 depicts; for instance, under supply, it starts from extraction and treatment, followed by primary energy supply, then import or export stock changes. At the primary energy supply, this is passed to conversion technologies, T&D system where both are transformed with some energy loss. At that point of T&D system provides final energy, to end use appliance with some energy loss to finally useful energy for consumption.
Various methods have been suggested to delay the degradation of battery capacity, including power management and the use of session-based activities. These approaches sometimes use low-current wireless transceiver techniques, the components of which can be turned off to save energy. In case the device reduces the power (similar in power efficiency) phase, the output of the device is significantly reduced versus when it is on due to the fifth-generation technology. Nevertheless, while sleeping, the device cannot relay or recognize the data packet. The task loop completes in correlation to the time; the device is on, then it rests before it finally turns off. The use of protocols running at a relatively low power level seems to be an acceptable explanation that accords with long-lasting WSNs (Yetgin et al., 2017).
Dependable IoT devices are required to generate correct data in several computations, its components are illustrated in Figure 2. The authors of this study presented an approach for characterizing IoT dependability measures. The reliability measurements are computed utilizing queuing theory. The theory explains the response time, queue length, delay time or waiting time, and busy periods, for example in recommender system, among others. To account for the reliance on items in IoT contexts, the Markov Chain traits were used, and thus better reliability measures were obtained (Zin et al., 2018).
Figure 2. Components of an IoT platform