###### Abstract  
Wireless Sensor Networks (WSNs) and the Internet of Things (IoT) have emerged as transforming technologies, bringing the potential to revolutionize a wide range of industries such as environmental monitoring, agriculture, manufacturing, smart health, home automation, wildlife monitoring, and surveillance. Population expansion, changes in the climate, and resource constraints all offer problems to modern IoT applications. To solve these issues, the integration of Wireless Sensor Networks (WSNs) and the Internet of Things (IoT) has come forth as a game-changing solution. For example, in agricultural environment, IoT-based WSN has been utilized to monitor yield conditions and automate agriculture precision through different sensors. These sensors are used in agriculture environments to boost productivity through intelligent agricultural decisions and to collect data on crop health, soil moisture, temperature monitoring, and irrigation. However, sensors have finite and non-rechargeable batteries, and memory capabilities, which might have a negative impact on network performance. When a network is distributed over a vast area, the performance of WSN-assisted IoT suffers. As a result, building a stable and energy-efficient routing infrastructure is quite challenging in order to extend network lifetime. To address energy-related issues in scalable WSN-IoT environments for future IoT applications, this research proposes EEDC: An Energy Efficient Data Communication scheme by utilizing \"Region based Hierarchical Clustering for Efficient Routing (RHCER)\"--a multi-tier clustering framework for energy-aware routing decisions. The sensors deployed for IoT application data collection acquire important data and select cluster heads based on a multi-criteria decision function. Further, to ensure efficient long-distance communication along with even load distribution across all network nodes, a subdivision technique was employed in each tier of the proposed framework. The proposed routing protocol aims to provide network load balancing and convert communicating over long distances into shortened multi-hop distance communications, hence enhancing network lifetime.The performance of EEDC is compared to that of some existing energy-efficient protocols for various parameters. The simulation results show that the suggested methodology reduces energy usage by almost 31% in sensor nodes and provides almost 38% improved packet drop ratio. IoT applications; clustering; energy efficiency; hierarchical framework; WSN-IoT; future communication 2023238839 2323218839 232323 2323 23 2323 2323 2323 2323 2323 2323 2323 2323 2323 2323 2323 2323 2323 2323 2323 2323 2323 233 2323 2323 233 233 233 233 233 233 233 233 23  
recharged. Although energy-harvesting systems exist, they cannot eliminate the necessity for energy management. As a result, the most difficult task is to organize the limited battery power by adopting energy-effective protocols for WSNs. WSNs are used for a variety of purposes, including military surveillance, remote patient monitoring in healthcare, measuring environmental temperature, humidity, light, pressure, monitoring machinery in industries, and so on [3; 4; 5]. WSN design difficulties include energy conservation, scalability, data aggregation and compression, security, routing, resource constraints, and so on. To overcome these design challenges, a multidisciplinary approach involving hardware design, networking protocols, algorithm development, and domain-specific knowledge is required. The goal of research in these areas is to produce robust and efficient solutions that allow for the effective deployment of wireless sensor networks across a wide range of Future IoT applications. Because sensor nodes are self-contained devices that rely entirely on their batteries to function, several academicians have recently been investigating energy-efficient clustering and routing strategies to reduce energy usage in sensor nodes.