Journal of Pharmaceutical Negative Results ¦ Volume 13 ¦ Special Issue 6 ¦ 2022 1683 An Improved Energy Efficient Solution for Routing in IoT Dr. Srinivasa Babu Kasturi 1 , P. Venkateswarlu Reddy 2 , Dr. K VenkataNagendra 3 , Dr. M. Radha Madhavi 4 , Dr. Sudhanshu Kumar Jha 5* 1 Professor, Department of Computer Science and Engineering, Nalla Narasimha Reddy Education Society’s Group of Institutions, Hyderabad, TS, India 2 Assistant professor, Department of CSE, Sree Vidyanikethan Engineering College, Tirupati, AP, India. 3 Professor, Dept. Of CSE, Guru Nanak University, Hyderabad, TS, India. 4 Department of Engineering Mathematics, College of Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India. 5 Assistant Professor, Department of Electronics and Communication, University of Allahabad, Prayagraj, Uttar Pradesh - 211002, India Email: sudhanshukumarjha@gmail.com DOI: 10.47750/pnr.2022.13.S06.221 The concept of the Internet of Things (IoT) is an innovation paradigm that suggests linking physical devices together to share data and work toward a common goal. Nodes in an IoT network are anticipated to communicate with one another and with third-party Internet services. However, not all network nodes have direct Internet access due to high deployment costs. As a result, additional network nodes should be using Internet-connected nodes as gateways to transmit data to online services. Due to its central role in establishing connections between nodes in a network and distributing data packets, routing protocols have emerged as a significant challenge in IoT use cases. The work of routing is complicated in mobile IoT scenarios due to the topology changes brought on by the mobility of nodes. To better handle the mobile nature of the devices, existing Iot routing solutions typically exhibit severe constraints and poor performance in such cases. This study proposes an improvement to the existing protocols; the Cluster Formation Protocol with Neuro Fuzzy Rules, in light of the fact that main routing techniques for low-power network are unable to achieve adequate performance in the shown IoT context. The energy efficiency of the routing process in WSN can be improved with the help of cluster based routing thanks to the proposed efficient routing algorithms. In addition, the efficiency of clustering & cluster based routing protocols can be enhanced by employing intelligent approaches like fuzzy rules, temporal constraints, and categorization via deep learning. Therefore, the safe transfer of data packets from of the source point to the sink node necessitates careful consideration in the development of cluster dependent routing algorithms. The cluster dependent routing method presented is developed, evaluated with respect to a number of criteria, and shown to be effective. Keywords: Wireless Sensor Networks (WSN), IoT, load balancing, Routing. 1. INTRODUCTION IoT has emerged as a key technology in numerous fields over the past decade [1,2], including "smart" buildings, "smart" cities, "smart" grids, "smart factories," and more. The Internet of Things (IoT) is the networked, connected & cooperative use of diverse physical objects and technologies for a variety of applications [3-5]. This includes but is not limited to mobile phones, sensors, cameras, actuator, and Broadcast Identification (RFID) tags. Some Internet of Things use cases, like smart houses and smart cities, require copious amounts of data for monitoring and controlling a defined region [5,6]. However, Wireless sensing networks (WSNs) are useful for monitoring and regulating a specific region because they provide a framework for managing and constructing the sensor nodes. [7-9]. Sensor nodes are thus regarded as primary building blocks of the IoT architecture in such contexts. Deployed sensor nodes in a WSN monitor and gather data about their surrounding environment, then relay that information to a ground station or sink that is hooked up to the internet via gateways [10,11]. IoT devices in WSN-based IoT networks have challenges in areas including radio range & processing power. Unfortunately, sensor nodes have a finite power supply, typically an irreplaceable battery [12-14]. Constant efforts to extend the lifespan of the network make conserving the power of the sensing nodes a top priority [15,16]. Green Internet of Things (IoT) systems necessitate a routing approach that takes into account not only the overall energy consumption of every node, but also the energy consumption of every node individually. The warm or energy gap problem [17,18] arises if this is not the case.