## 1 Introduction
This is because environmental factors such as weather and seasonal constraints heavily determine the energy harvesting operational technique [4; 5]. In addition, the size an EH device may trigger deployment issues especially in a situation where the size of the EH device is much larger than the sensor node that it is trying to power. One of the major limitations of the single data mule scheme is that sensor nodes are battery-powered and highly irreplaceable owing to the very large associated costs and mode of deployments. A major challenge of the data collection and transmission operations of a WSN as depicted in [4; 8; 9; 10; 11], is the finite node-lifetime of the WSN, where the sensor-nodes are mostly energy-constrained and require to use energy to transmit their data to the mobile data collectors. This invariably is a fundamental performance bottleneck of the data mule system which tends to minimize the node energy consumption by transferring the transmission protocol overheads at the sensor to the mobile data collectors. One of the major objectives of the present study is to address this challenge--to make WSNs perpetually operational by proposing approaches that tend to replenish the energy of the battery-powered sensors used in data collection and transmission operations. Hence, the need for the proposed WPT technique. By considering both techniques (i.e., exploiting the same data collectors as wireless energy transmitters), we intend to maximize the network lifespan, further minimize the node energy consumption of the sensors, reduce cost of deployments and optimize collection efficiency. Given the constraints on energy supply and data transmission performance of the sensor nodes it is, therefore, important to optimize the energy transfer strategy of the wireless energy transmitters as well as the average energy charged by the sensors. Therefore, our proposed scheme intends to leverage on the advantages of the combinatorial nature of these two identified separate schemes to further minimize cost, prolong the network lifespan and optimize energy efficiency. The major contributions of this paper are as follows:  
* This article is structured to first give a comprehensive review of WPT technologies and applications that can be exploited for SC scenarios and highlights a comparative analysis of the various WPT technologies to determine the most energy-efficient for IoT and WSN applications. * We closely re-examine the different application models of WPT technologies with the objective of identifying which application is best suited or closely matched with our proposed scheme for IoT-SC applications. * Leveraging on the advantages of WPT technology, we address a major limitation of the data mule system by proposing a new scheme which exploits the use of MDCs (data mules) for both data collection and wireless energy transmission operations in a SC. * We conduct an empirical study of WPT model to determine the effect of varying the distance on the power transfer efficiency. We investigate using simulations the WPT efficiency and the average energy charged by the sensors while considering different trade-offs. The rest of this paper is organized as follows. Section 2 presents the background and motivation of the study, while Section 3 presents a comprehensive review of WPT technologies that are applicable for IoT/WSN SC scenarios. In Section 4, we present the different application models of WPT technologies. We investigate the WPT efficiency and the average energy charged by the sensor-nodes of a power-hungry opportunistic IoT network by considering different trade-offs. Section 5 presents problem description, formulation and solution, while Section 6 presents simulation results and analysis. Finally, Section 7 concludes the work.