The agricultural sector is a major economic force in Sri Lanka, which contributes to the national economy, food security, and employment. The traditional methods practiced by farmers mainly drove the growth of the agriculture sector over the last 2500 years. However, these traditional methods have often been ineffective against pest attacks in recent years causing significant losses to farmers and threatening food security. To counter these issues, officials and researchers have started formulating novel technology-based smart solutions. This study proposes a smart, autonomous mobile robot that can help detect pests and diseases in advance and assist in crop estimation of chili plants. The model is created as such for pest and plant disease detection in small-scale chili plantations with the hope of using it in other crop types for the same purpose in the future. Thus, the proposed approach together with the developed model can be used to enhance the growth of other plants as well. Identification of the type of garden and the detection of pests and plant diseases are achieved using machine learning techniques while the identification of nutrient deficiencies is achieved using image processing techniques. This proposed mobile robot incorporates sensory inputs, machine learning, robotics, and image processing. Furthermore, a mobile application acts as the interface between the user and the robot.