###### Abstract  
The Internet of Things (IoT) integrates different advanced technologies in which a wireless sensor network (WSN) with many smart micro-sensor nodes is an important portion of building various IoT applications such as smart agriculture systems, smart healthcare systems, smart home or monitoring environments, etc. However, the limited energy resources of sensors and the harsh properties of the WSN deployment environment make routing a challenging task. To defeat this routing quandary, an energy-efficient routing protocol based on grid cells (EEGT) is proposed in this study to improve the lifespan of WSN-based IoT applications. In EEGT, the whole network region is separated into virtual grid cells (clusters) at which the number of sensor nodes is balanced among cells. Then, a cluster head node (CHN) is chosen according to the residual energy and the distance between the sink and nodes in each cell. Moreover, to determine the paths for data delivery inside the cell with small energy utilization, the Kruskal algorithm is applied to connect nodes in each cell and their CHN into a minimum spanning tree (MST). Further, the ant colony algorithm is also used to find the paths of transmitting data packets from CHNs to the sink (outside cell) to reduce energy utilization. The simulation results show that the performance of EEGT is better than the three existing protocols, which are LEACH-C (low energy adaptive clustering hierarchy), PEGASIS (power-efficient gathering in sensor information systems), and PEGCP (maximizing WSN life using power-efficient grid-chain routing protocol) in terms of improved energy efficiency and extended the lifespan of the network. Internet of Things; wireless sensor networks; energy-efficient; clustering routing protocol; grid-based; data fusion; chain-based +
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layer as well as avoid network congestion [14]. This work can be performed by smart IoT devices such as routers, sinks (or base stations), gateways, or servers equipped with strong processing capabilities, big memory, and unlimited power resources [15; 16; 17]. The networking layer is where the sensor devices can be deployed in the real environment to measure diverse physical phenomena (e.g., temperature, humidity, air pressure, rainfall, etc.) connected to WSNs [18; 19]. A WSN comprises wireless sensor devices that sense, collect, and detect environmental conditions. Usually, sensor devices use a wireless channel to communicate with a sink or gateway device connected to the Internet through fog servers. Moreover, smart sensor devices have a cheap price, small size, and limited battery energy. This battery energy resource is particularly hard to recharge or replace during operation time after deploying in a harsh area where humans are inaccessible. In such conditions, if the sensors' energy is exhausted, the network lifespan and quality of services will be strongly decreased or the WSN will be stopped [20]. Therefore, utilizing energy efficiency is a crucial task for designing routing protocols in WSN-based IoT applications to balance energy consumption and maximize network lifespan (NL), thereby improving the service quality of WSN-based IoT applications. The clustering hierarchical routing technique such as LEACH [21] and PEGASIS [22] has proven to be a good solution to preserve battery energy resources and prolong NL, in which sensor nodes are grouped into several clusters. Each cluster contains one cluster head node (CHN) and one or more member nodes (MNs). The CHNs are responsible for controlling the operations in their cluster, such as receiving data, fusing data, and forwarding the aggregated data to the sink device. The MNs only communicate with their CHN. After an interval of time, the role of the CH should be transferred to another node in order to balance the nodes' energy consumption in the network [23].