DESIGN AND FABRICATION OF ROV FOR PEST AND DISEASE CONTROL IN MANGGO FARM AT KOTA SARANG SEMUT, KEDAH STATE, MALAYSIA

Agriculture is an important sector in Malaysia, contributing to the country’s gross domestic product (GDP) and providing employment opportunities for its people. The rural development plan also shifted its focus to the agricultural sector. On the other hand, economic diversification has recently shifted from agriculture to manufacturing and service industries. Comprehensive reforms are needed to revitalise Malaysia’s agricultural economy through the implementation of smart agriculture. Traditional agricultural methods pose numerous challenges to farmers, including physical and toxic hazards from the environment. These hazards can lead to heat stroke, death or injury due to unknown hazards during manual labour, and poisoning during crop fertilization. Incomplete equipment can also cause skin and respiratory diseases. Traditional agriculture is inefficient, taking a long time to harvest crops, which can lead to food production failing to keep up with consumption and importing more food from other countries. This unbalanced trade between countries will also be unavoidable. Therefore, it is crucial for farmers to adopt more sustainable and efficient methods to mitigate these potential risks. This research proposes a remote-control spraying robot design, also known as ROV robot pest nutrition robot, which aims to prevent pesticides from directly contacting the human body in agricultural production and improve the efficiency of agricultural spraying operations. The study focuses on three main tests to validate the functionality and effectiveness of fabricated prototypes and systems. The first test validates an online digital image processing method for disease identification and categorization using Fast k-Means Clustering. The second test integrates a real-time robotic monitoring system using LoRa technology, involving a mobile robot and a mixer station. The final test evaluates the automatic production system of pesticide mixture composition using LoRa technology. The online digital image processing method was tested on a mango tree using the mobile robot monitored from the control centre using LoRa and the result was portrayed. Clearly shown that the proposed method capable detecting the different disease online using LoRa. The sample was infected by anthracnose and die black disease. The online monitoring system allowed the operator to control the robot’s movement, detection of diseases and spray of pesticide and fertiliser in real time from the control centre using Lora. The RSSI value recorded from Pusat Teknologi Mempelam Sala Kanan, shows that there is proportional relation between the ‘ping’ speed/ tag speed with distance. Furthermore, this results also indicates that the longest ‘ping’ speed approximately 500 μ second at distance of 287 m. The mixer station consists of four 80l tanks controlled by LoRa from the control centre. Each tank is assisted by a pump (4.7l/m, 12 V, 2.3A) and a motor (12V, 350 W, 7A) whereas the motor able to mix the pesticide/fertiliser evenly, ensuring efficient operation. The operator can direct the robot to replace the work of the worker, and the robot has a camera as a monitoring device. The agricultural sector, producers and consumers have all benefited from this research. This research also predicts potential future trends. This research has the potential to improve people’s lives by advancing technology and innovation, as well as promoting economic and environmentally responsible growth.