The battery power limits the energy consumption of wireless sensor networks (WSN). As a result, its network performance suffered significantly. Therefore, this paper proposes an opportunistic energy-efficient routing protocol (OEERP) algorithm for reducing network energy consumption. It provides accurate target location detection, energy efficiency, and network lifespan extension. It is intended to schedule idle nodes into a sleep state, thereby optimising network energy consumption. Sleep is dynamically adjusted based on the network’s residual energy (RE) and flow rate (FR). It saves energy for a longer period. The sleep nodes are triggered to wake up after a certain time interval. The simulation results show that the proposed OEERP algorithm outperforms existing state-of-the-art algorithms in terms of accuracy, energy efficiency, and network lifetime extension.

The Internet of Things (IoT) enabled wireless sensor network (WSN) is now widely employed in various sectors like smart city and vehicle transportation for their expanded capabilities such as data storage, access, and monitoring. The use of smart sensors that continuously collect data from the smart environment makes these possible. Furthermore, these facilitate the easy access of stored data over a secure IoT-gateway for mobile users. This device mobility that allows shifting to multiple locations, makes it challenging to route data across many access points. In this regard, it induces packet loss and improper node selection, which could result in connection failure and network unreliability. This study proposes a new data routing protocol called as Fuzzy Logic Nodes Distributed Clustering for Energy-Efficient Fault Tolerance (F-NDC-EEFT). It can be deployed on any network platform, including mobile and non-mobile nodes. It considers performance metrics such as delivery rate, withstand node aliveness, communication delay, and energy efficiency to find an optimized path for the better performance of IoT enabled WSNs. The clustering approach is applied to the instant data load, which divides it into the distinct node groups. When proposed algorithm is tested alongside existing routing protocols for performance, it is found to save energy, minimize the number of connection failures, boost the throughput, and increase the network’s lifetime.