## 3 Overview of Multihop CA-IoT Architectures and Testbeds
\begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**Author/Yr** & **Comm. Tech** & **Routing Architecture** & **Deployment (Indoor/Outdoor)** & **Hop Type** & **Problems Addressed** & **Issues** \\ \hline Ref. [14], 2006 & ZigBee & Mica2 clones hardware and TinyS software/centralized, flooding & Outdoor & Single-hop & Precision farming to gather real-world experiences & Relies on a fixed support system, is expensive, power-inefficient, and location-restricted achieved due to high network complexity \\ \hline Ref. [3], 2017 & ZigBee & IEEE 802.15.4/centralized, flooding & Outdoor & Single-hop & Disease control & Relies on a fixed support system, is expensive, power-inefficient, and location-restricted \\ \hline Ref. [21], 2017 & Wi-Fi & Centralized with one SN via 6 LoWPAN & Indoor & Single-hop & Monitors farms with a camera and soil temperature and humidity using CC3200 single-chip & Location-restricted due to Wi-Fi \\ \hline Ref. [5], 2018 & ZigBee & Flooding-based & Indoor & Single-hop & Data outlier detection and decision support system for precision irrigation testbeds & Results based on 3 SNs under unrealistic indoor conditions \\ \hline Ref. [15], 2018 & Wi-Fi-based & 6 LoWPAN, 6 LBR, and centralized, flooding & Indoor & Single-hop & Latency improvement via fog computing & Capital-intensive, energy-inefficient, high-complexity, and location-restricted \\ \hline Ref. [24], 2018 & Arduino Uno with Wi-Fi/3G/4G & Centralized one-SN architecture & Indoor & Single-hop & Monitors environmental conditions & Location-restricted due to Wi-Fi and high complexity when the network scales \\ \hline Ref. [31], 2019 & ZigBee & Centralized, flooding & Indoor and outdoor & Single-hop & Gathers real-world deployment experiences & Results focused on mere observation rather than real-world deployment scenarios \\ \hline Ref. [28], 2020 & NodeMCU with Wi-Fi & Centralized one-SN architecture & Indoor & Single-hop & Monitors environmental conditions & Location-restricted due to Wi-Fi and high complexity when the network scales \\ \hline Ref. [26], 2023 & Arduino Uno with GSM & Centralized one-SN architecture & Indoor & Single-hop & Monitors environmental conditions & Location-restricted due to Wi-Fi and high complexity when the network scales \\ \hline Ref. [20], 2024 & Esp32 with Wi-Fi and ASR605/x & Centralized one-SN architecture & Outdoor & Single-hop & Creates a cheaper IoT SN with easier data storage and processing steps & Location-restricted due to Wi-Fi and high complexity as the network scales \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparative assessment of benchmarking Agri-IoT testbed solutions. by reducing data inconsistency errors and minimizing the power wasted on transmitting redundant, long-range data to the BS. The BS can either process the received data and make local actionable decisions to actuate the irrigation system or send the raw/preprocessed data to the IoT cloud for further processing and return the actionable decisions to the BS for execution. The resulting actuation signal is then sent to the pump for precision irrigation or chemical application. Data copies can be stored in the IoT cloud for remote monitoring/control or further analysis to identify field climate patterns for automating the irrigation system. Since communication is the principal power consumer in WSN-based CA-IoT networks, and its key factors (i.e., distance and packet size) can be optimally managed through a cluster-based architecture [17; 55; 56; 57; 58], this architecture is deemed optimal for power optimization in these networks. Despite the advantages of a cluster-based architecture for WSN-based Agri-IoT applications [9], this claim remains unvalidated due to insufficient research on hardware evaluation and the exploration of its untapped potential, especially within the MCA-IoT architecture.