The performance of Wireless Sensor Networks (WSNs) faces a number of challenges. Of these challenges, energy consumption is considered a hot research area. Most WSN energy is used in transmitting the data from the sensor nodes either among each other or to a Base Station (BS). For this reason, many routing protocols have been developed to facilitate the data dissemination in the WSNs. One of these protocols, Low Energy Adaptive Clustering Hierarchy (LEACH) has provided a distinctive hierarchical approach that efficiently forwards the nodes data to the BS, but it suffers from increased energy consumption and a significant decline in the network performance in the case of large-scale networks. This paper aims to present a new approach for splitting the whole sensor network into several levels. Thus, every node will be acting accordingly on its position and status. Further, two techniques, a static one and a dynamic one, have been developed to route the data between the levels. The simulation results demonstrated that the proposed techniques prolong the lifespan, improve the stability and raise the throughput of the network compared with the LEACH, the Improved MHT-LEACH (IMHT-LEACH), and the Enhancing DMHT-LEACH (EDMHT-LEACH) protocols.
The transport sector is a major consumer of energy, and thus a major contributor to greenhouse gas (GHG) emissions. The introduction of Electric Vehicles (EVs) has helped in mitigating some of the energy demands presented by the transportation system, though the electrical energy still needs to be secured through conventional and renewable resources. Searching for a new power source for vehicles has become necessary, due to incentives and policy initiatives to counter fossil greenhouse gas emissions. This study provides a new efficient Photovoltaic (PV) powered transportation system, which may be utilized instead of traditional public transportation systems. The main idea is to transform the transportation systems used by large campuses into green systems by deploying educated scheduling approaches and utilizing existing renewable energy infrastructures. The German Jordan University (GJU) campus was chosen as a case study. The presented work describes a comprehensive methodology to exploit the full capacity of the existing PV power plant coupled with the rescheduling of the transportation fleet to meet the energy availability and consumption demand. The proposed technique audits the existing renewable energy power plants for optimum operation. The results validate the efficiency of the proposed system and its ability to reduce carbon dioxide (CO2) emissions compared to traditional transportation systems with an acceptable payback period.
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