# Evaluation of Green Strategies for Prolonging the Lifespan of Linear Wireless Sensor Networks
## 6 Energy-Harvesting Techniques  
This section presents the energy-harvesting techniques aimed at prolonging the lifespan of WSNs and evaluates their effectiveness in LWSNs. While energy-saving techniques offer the potential to prolong the lifespan of WSNs, it is crucial to acknowledge that sensor nodes relying on batteries cannot ensure uninterrupted monitoring over extended durations. This constraint stems from the finite capacity of batteries, which inevitably deplete over time. This challenge is especially pronounced in WSN applications where nodes may be situated in physically inaccessible locations. In such cases, the logistical and cost-related obstacles associated with battery replacement become substantial. Despite the available techniques to mitigate power consumption, the reliance on battery power imposes constraints on the operational lifespan of the system, necessitating periodic battery replacements or recharging [120]. Additionally, the monitoring process is interrupted during battery replacement, resulting in downtime [121]. To address these limitations, energy-harvesting techniques emerge as a viable solution [48]. By harnessing ambient and/or external energy sources from the environment, these techniques offer a means to replenish the energy consumed by sensor node batteries [122]. Implementation of energy harvesting not only mitigates the constraints posed by a finite battery life but also enhances the sustainability and longevity of WSNs [49], especially in remote or difficult-to-access deployment scenarios like border surveillance and highway, railway, powerline, and pipeline monitoring. Energy-harvesting (EH) techniques convert energy from external sources, which are non-renewable, or from ambient environment sources, which are renewable, into electrical energy that can be used to power autonomous devices such as wireless sensor nodes [37; 122]. While numerous existing EH systems produce only a restricted amount of power, in the order of \(\mu\)Wcm\({}^{-2}\) to mWcm\({}^{-2}\), the increasing popularity of EH is attributed to advancements in very low-power sensors and wireless communication systems [123]. The energy harvested from external and ambient sources is used to replenish the energy depleted by the sensor node. This ensures that the battery energy of the sensor nodes is not depleted and thus prevents the development of an energy hole in the WSN. This increases the lifetime of the nodes and that of the WSN as a whole, thus preventing frequent battery replacement in most applications. Thus, the goal of EH techniques is to convert energy from one form to another that can be used to power sensor nodes and thus extend the lifetime of the WSN [124]. The source from which energy is harvested in a WSN is a valuable resource since it determines the amount of energy available to the network and the rate of conversion from the source to electrical energy [37]. This makes the ambient sources which are accessible within an environment and which do not need any external energy supply very attractive to WSN applications. Table 7 presents a comparison of the different energy-harvesting techniques based on energy sources, conversion materials, conversion mechanisms, typical power densities, and conversion efficiency. A taxonomy for classifying energy harvesters is presented in Figure 8. The ambient (renewable) sources consist of flow (wind and hydro), solar (outdoor), thermal (geothermal), and ambient RFs. These sources are also referredto as primary or renewable sources because they can be replenished over time through natural processes [48]. Energy harvesting from ambient sources plays a crucial role in prolonging the lifespan of WSNs for two primary reasons. Firstly, energy harvested from the environment is pollution-free, contributing to environmentally sustainable operations. Secondly, as a renewable resource, it offers the potential for devices to operate unattended for virtually unlimited periods, enhancing the autonomy and longevity of WSNs.