Development of an IoT-Driven Smart Agricultural Management System Using Mecanum Drive Robotic Arm Manipulators for Precision Farming: A Systematic Literature Review

The Internet of Things (IoT), robotics, and artificial intelligence have only recently converged in agriculture, driven by the need for sustainable, resilient food systems. Precision farming demands real-time physical action, not just data-driven insight, yet existing agricultural robotic systems rarely integrate omnidirectional mobility, dexterous manipulation, and environmental awareness for complex tasks in unstructured farming environments. This systematic literature review examines the state of the art in IoT-enabled smart agricultural management systems that combine Mecanum-wheel mobile platforms with multi-degree-of-freedom (DoF) robotic arm manipulators. Following the PRISMA 2020 guidelines, we analysed 81 peer-reviewed articles (2015–2025) from Scopus, Web of Science, and IEEE Xplore. By design, every included study employs Mecanum-wheel mobility, since this was a required inclusion criterion; this reflects our deliberately narrow scope rather than the adoption rate of Mecanum wheels in agricultural robotics generally, which the wider excluded literature suggests remains comparatively low. We synthesise key mathematical models, Mecanum inverse/forward kinematics, 6-DoF Jacobian matrices, LoRaWAN link budget analysis, and closed-loop PID control across sensing, mobility, manipulation, integration, and validation. This synthesis reveals five recurring limitations: poor terrain adaptability of Mecanum rollers in muddy fields, communication latency exceeding 1 s in long-range protocols, absent force feedback in most manipulator designs, and 28–42% performance degradation under field versus laboratory conditions. Few studies report true closed-loop operation where sensor data directly triggers robotic action, and smallholder farmers, particularly in developing economies such as Nigeria, remain excluded from these technologies due to cost, energy, and usability barriers. To address these gaps, we propose a modular system architecture featuring solar-assisted Mecanum mobility, a 6-DoF force-controlled arm with quick-change end-effectors, hybrid LoRaWAN/Wi-Fi 6 communication, edge AI (NVIDIA Jetson), and a multilingual cloud dashboard laying a foundation for scalable, inclusive agricultural robotics. This proposed architecture is a conceptual direction motivated by the review’s findings and is not itself an empirical outcome of the systematic review.