## 2 Background and Synthesis of Related Literature  
### Background  
Over the past decade, human survival has increasingly been jeopardized by factors such as population growth, climate change, and dwindling water resources, leading to significant food insecurity [37]. In response to these challenges, the development of smart and eco-friendly Agri-IoT technology has emerged. This technology is designed to enhance precision farming and greenhouse management, thereby improving food production and crop quality on limited land. By leveraging wireless sensor networks (WSNs), Agri-IoT represents a shift from personal computing to ubiquitous computing, offering enhanced flexibility and simplicity for remote monitoring, system control, and environmental management [3; 39; 40]. The WSN-based Agri-IoT system, as illustrated in Figure 3, operates as a feedback control mechanism for comprehensive farm management. It facilitates real-time monitoring, data sampling, resource optimization, and automation of agricultural operations, such as precision irrigation and disease management [4]. This system relies on a network of battery-powered, wirelessly connected SNs equipped with sensing, processing, and communication capabilities [39; 41; 42]. These SNs are spatially distributed and self-configured to enable efficient remote sensing, surveillance, and control through automated data collection and processing [43; 44]. Figure 2 shows that a typical WSN-based Agri-IoT network includes field-deployed SNs, a base station (BS) or gateway, and IoT cloud servers that host data analytics engines and user control applications. This architecture allows users to monitor farm conditions and execute control actions via software interfaces such as web pages or custom apps. The routing architectures employed in WSN-based Agri-IoT include a cluster-based routing architecture, a centralized routing architecture, and a flooding-based routing architecture, as illustrated in Figure 4. The system's ability to provide real-time monitoring and control is a significant advancement over traditional farming practices. Despite these advancements, Agri-IoT technology has not fully realized its potential due to several challenges. Existing solutions often suffer from high costs, location dependence, and complexity in deployment and management. Additionally, they rely on centralized or mesh-like communication architectures that are neither scalable nor fault-tolerant, as illustrated in Figure 5. Agri-IoT systems must address unique constraints such as battery power limitations, cost efficiency, and the need for fault tolerance, making the choice of routing architecture critical for overcoming these challenges [4; 8; 45; 46; 47; 48; 49]. Figure 4: Sample network architectures: centralized data-centric, cluster-based, and graph/flooding-based architectural frameworks [10; 50]. Figure 3: Conceptual framework: Agri-IoT-based farm monitoring and control cycle [9; 10]. The cluster-based multihop architecture is particularly well suited to address these challenges. Unlike centralized architectures, which are prone to bottlenecks and inefficiencies in larger networks, and decentralized flood-based architectures, which still face some centralized issues, the cluster-based approach organizes SNs into clusters with an elected cluster head (CH). This arrangement reduces intra-cluster communication distances, improves energy efficiency, and enhances fault tolerance by distributing the communication load and managing data locally before transmission [4; 8; 17; 38]. Therefore, the cluster-based multihop architecture is ideal for creating robust, cost-effective, and easy-to-manage Agri-IoT networks that can be deployed and operated effectively in agricultural environments. To date, Agri-IoT technology has struggled to achieve its transformative potential in agriculture due to several factors.