Mobile robots are increasingly being applied in a variety of sectors, including agricultural, firefighting, and search and rescue operations. Robotics and autonomous technology research and development have played a major role in making this possible. Before a robot can reliably and effectively navigate a space without human aid, there are still several challenges to be addressed. When planning a path to its destination, the robot should be able to gather information from its surroundings and take the appropriate actions to avoid colliding with obstacles along the way. The following review analyses and compares 200 articles from two databases, Scopus and IEEE Xplore, and selects 60 articles as references from those articles. This evaluation focuses mostly on the accuracy of the different path-planning algorithms. Common collision-free path planning methodologies are examined in this paper, including classical or traditional and modern intelligence techniques, as well as both global and local approaches, in static and dynamic environments. Classical or traditional methods, such as Roadmaps (Visibility Graph and Voronoi Diagram), Potential Fields, and Cell Decomposition, and modern methodologies such as heuristic-based (Dijkstra Method, A* Algorithms, and D* Algorithms), metaheuristics algorithms (such as PSO, Bat Algorithm, ACO, and Genetic Algorithm), and neural systems such as fuzzy neural networks or fuzzy logic (FL) and Artificial Neural Networks (ANN) are described in this report. In this study, we outline the ideas, benefits, and downsides of modeling and path-searching technologies for a mobile robot.

This research focuses on the design and implementation of an Internet of Things (IoT) smart-based system for the agriculture industry, especially chilli plantations. Every year, chilli farmers experience huge losses due to pest infestation and a lack of technology to precisely manage their farms. To solve several problems, the IoT system was designed to continuously monitor pest detection status, temperature, humidity index, and soil moisture level simultaneously. Besides these, the IoT system is also designed for long-distance remote water, pesticide, and fertiliser pumps. An IoT platform was applied in this project to provide a monitoring dashboard and switches to empower several pumps with long-distance remotes using the LoRa communication systems in a wide coverage range of chilli farms. Three experiments were designed to determine the range of the LoRa network. All experiments and data collection were done on the campus of Universiti Teknikal Malaysia Melaka (UTeM) and the Melaka area. All experiments were analysed based on the results collected, such as packet reception rate (PRR), signal-to-noise ratio (SNR), and received signal strength indicator (RSSI). Based on the experiment results and conclusion, the LoRa communication system is suitable for applying to chilli farms in order to monitor all the elements such as soil moisture and pest detection status. The experiment also concludes that this LoRa network can be worked effectively up to cover a range of 260m with the elevation of the gateway. Keywords—Management systems; Internet of Things; crop field; LoRa; agriculture industries; precision engineering