Weather Monitoring for Curating Cricket Pitches using Machine Learning and Arduino

This paper introduces an innovative weather monitoring system developed for effective cricket pitch maintenance using machine learning algorithms and Arduino microcontrollers. The system is developed to tackle the challenge of unpredictable weather conditions, which can really affect the quality of pitches and the safety of the players. Using a number of sensors monitoring environmental parameters such as temperature, humidity, soil moisture, and rainfall, it will give real-time information to the curator of the pitch for a healthy and pitch-conditioning regimen. The tailoring of such data analysis techniques through machine learning offers precise and actionable recommendations for effective pitch keeping by a groundsman. Interventions at appropriate times that suggest the time, along with the ability of the system to predict weather, would be a huge improvement to look after the sporting environment, and in return, it assures the safety and quality of the play. This current study will show the potential of upgraded technology in making cricket pitch maintenance more efficient and effective for both the players and the audience and for the curators.