## 2 Background and Synthesis of Related Literature
### Synthesis of Related Literature  
Within the evolving landscape of agriculture, Agri-IoT represents a transformative paradigm designed to address various field-specific challenges through diverse technological solutions. By leveraging embedded WSNs and actuators, Agri-IoT facilitates the collection and management of farm data, thereby optimizing farming processes such as resource management (e.g., water and fertilizer optimization), irrigation control, and soil management. This technology enables farmers to remotely monitor and manage their crops and livestock using smartphones, potentially reducing production costs and enhancing productivity on limited land. However, the combined effects of climate change and rapid global population growth impose significant constraints on resources such as land, water, nutrients, and labor, necessitating improved resource management and waste reduction. In response to these challenges, the United Nations has urged researchers to focus on developing contextually relevant Agri-IoT solutions capable of increasing food production by 70% by 2050 to meet the demands of a growing population [20; 21]. Nonetheless, current research has predominantly centered on location-constrained and costly testbeds, which are primarily effective under indoor conditions. The following challenges have been identified in the existing literature:  
Figure 5: Taxonomy of Agri-IoT design challenges [9; 10]. 1. **Unique Agricultural Settings:** The agricultural setting is a unique area where conventional IoT technologies do not apply. For instance, existing Agri-IoT solutions are location-constrained because they are based on costly Wi-Fi or cellular communication technologies that require reliable on-farm electricity and internet coverage, which are generally not available in Africa. This necessitates a solution based on affordable battery-powered SNs. These Agri-IoT applications mainly utilize architecture-restricted, high-resource-demanding routing techniques (e.g., routing over low-power and lossy networks protocol (RPL)) and communication standards (e.g., 4G, 5G, ZigBee, NB-IoT, Wi-Fi, and long-term evolution (LTE)) [51], which are difficult to access on typical African farms. Additionally, the users of Agri-IoT technologies are low-income earners with limited technological expertise. As a result, there is a pressing need for contextually relevant, affordable Agri-IoT solutions that are easy to deploy and manage, battery-powered, and leverage freely available technologies without licensing requirements. This study addresses these challenges by focusing on low-power communication technologies, power optimization, and cost-effective, scalable solutions [4; 8; 17]. 2. **Susceptibility to Faults and Failures:** Agri-IoT networks are prone to faults and failures due to the dense deployment of resource-constrained SNs in harsh environments, where they operate autonomously with minimal post-deployment maintenance. Effective network supervisory protocols must incorporate power optimization, fault management, and self-adaptability. The multihop cluster-based architecture has been identified as a promising routing protocol for addressing these issues [3; 4; 8; 9; 17]. However, the lack of comprehensive, contextually relevant hardware validation for multihop CA-IoT networks results in abrupt failures in many existing testbed solutions [3; 5; 14; 15; 16; 31]. 3. **Inadequate Consideration of Communication Technologies:** Existing Agri-IoT studies often emphasize high-power-demanding communication technologies (e.g., Wi-Fi and cellular technologies), centralized ZigBee standards, and conventional IoT principles [3; 5; 14; 15; 19; 31]. Although theoretical studies suggest that multihop cluster-based architectures are well-suited for Agri-IoT applications [4; 8; 17; 52], there is a lack of practical hardware implementation and performance evaluation for these architectures.