Robots, automation, the Internet of Things (IoT), and its application based on precision agriculture are essential to reduce the burden of peoples in farming. Making this method more effective depends on the addition of machine learning-based leaf disease detection. The farmer may end up saving time and effort, increasing output, and increasing efficiency as a consequence. The usage of multiple electronic sensors and cloud-based services in agriculture may also help with quick processing and accurate measurement of any parameter. A prototype agricultural rover with ploughing, seeding, and separate autonomous irrigation and fertilizer sprinkling systems was developed to ensure appropriate farming. The rover is managed by a smartphone using a Wi-Fi module. The automated irrigation and fertilizer dispensing systems include characteristics that may be shown on an OLED display and a cloud-based IoT analytics service called thing talk. Machine learning-based logistic regression is used with a number of adjustments to improve the accuracy of the diagnosis of leaf disease.