LAXMANA-REKHA MAPAKA: NO BALL PREDICTION MODULE FOR DOMESTIC CRICKET GROUND BY USING EMBEDDED CONTROLLERS

Abstract

Abstract The work promotes the design and development of a smart, economical and sensor based no-ball detection and prediction system for domestic cricket grounds. Equipped with sensors such as IR reflection sensors, ultrasonic sensors, helps to get the foot positions mapped accordingly. It is also equipped with digital sensors such as cameras, for the predictions to take place. The sensors run on a popular embedded controllers – Arduino uno and Arduino nano, while the digital camera runs on a ‘Raspberry pi 3-b’, which runs on a raspberry pi OS. The Raspberry pi, acts as a main computer, while the Arduino uno and the nano acts as a client. The raspberry pi runs a python script support by YOLOv8 – for object detection and tracking, and open-cv for no-ball detection. The main script is also supported by various other scripts, which helps in the smooth detection and prediction. The Arduino uno and Arduino nano are used for their speed and the handshake capability between the two boards. While the Arduino is a client, it’s also armed with critical interrupts, that helps to take its own decision. The client also controls a “Sensor safety box” – KAVACH, which is specially designed and completely operated by the client. The invention also contains an app called Dharmaraya, which is an app specially designed for umpires. Any player on-field can request a review for a no-ball, the umpire can review from the dedicated device, and give the decision. At current India is one of the highest performing team. To maintain the status quo, in terms of performance of the team, we need to contribute to the grassroot of cricket.

Specification

Description:LAXMANA-REKHA MAPAKA: NO BALL PREDICTION MODULE FOR DOMESTIC CRICKET GROUND BY USING EMBEDDED CONTROLLERS

FIELD OF INVENTION: ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING ON EMBEDDED SYSTEMS

Abstract
The work promotes the design and development of a smart, economical and sensor based no-ball detection and prediction system for domestic cricket grounds. Equipped with sensors such as IR reflection sensors, ultrasonic sensors, helps to get the foot positions mapped accordingly. It is also equipped with digital sensors such as cameras, for the predictions to take place. The sensors run on a popular embedded controllers - Arduino uno and Arduino nano, while the digital camera runs on a 'Raspberry pi 3-b', which runs on a raspberry pi OS. The Raspberry pi, acts as a main computer, while the Arduino uno and the nano acts as a client. The raspberry pi runs a python script support by YOLOv8 - for object detection and tracking, and open-cv for no-ball detection. The main script is also supported by various other scripts, which helps in the smooth detection and prediction. The Arduino uno and Arduino nano are used for their speed and the handshake capability between the two boards. While the Arduino is a client, it's also armed with critical interrupts, that helps to take its own decision. The client also controls a "Sensor safety box" - KAVACH, which is specially designed and completely operated by the client. The invention also contains an app called Dharmaraya, which is an app specially designed for umpires. Any player on-field can request a review for a no-ball, the umpire can review from the dedicated device, and give the decision. At current India is one of the highest performing team. To maintain the status quo, in terms of performance of the team, we need to contribute to the grassroot of cricket.
BACKGROUND OF THE STUDY
PRIOR ART OF WORK
The current technologies in domestic cricket grounds are not up the mark when compared to international grounds. This causes a major problem to both the players as well as the umpires. The major problem that we deal in these types of grounds is the pressure that is put on the umpire to take certain decisions. Some of these decisions may be career-changing for both the umpires and the players on the field. One such decision includes the no-ball (bowler's end) and LBW (leg before cricket). It is a known fact that the umpires in the domestic grounds are not well experienced in comparison to the international umpires, or sometimes even compared to national umpires. The umpire is pressurized to look both LBW as well as no-ball, there is a chance for human error in this scenario. While the umpires standing in both the national matches as well international matches there are aides for no-ball such as buzzers, alarms etc., but domestic cricket grounds lack those.
This is a problem for grassroot cricket, where good and potential players face problems. Our invention detects and predicts no-ball events during the play. The invention consists of a traditional integration of both embedded systems and AI for prediction and detections. The inventions have a minimal number of moving parts, has backup sensors. The AI model in the invention completely take the decision on its own, while it can also be reviewed by the umpires for transparency. This design is the future of domestic cricket grounds in India, as its economical reliable as well as smart. The decision taken by it are full-proof as it involves sensors such as IR sensors, ultrasonic sensors, while the AI is running on a dedicated raspberry pi, using a raspberry pi camera. This makes sure that even if any damage to any two sensors is made, the third one will kick up. The AI is not a backup, and runs parallelly with detection. Hence any damage to the raspberry pi-camara will result in loss of AI leading to loss of prediction, but will not lead to loss of no-ball detection.
Embedded systems
The textbook definition of embedded systems is "An embedded system is a combination of computer hardware and software designed for a specific function"
ARTIFICIAL INTELLIGENCE & MACHINE LEARNING (AI & ML)
Artificial Intelligence (AI) is the field of computer science that creates systems capable of performing tasks that typically require human intelligence, such as learning, reasoning, and problem-solving. Machine Learning (ML) is a subset of AI where algorithms learn from data to make decisions or predictions without being explicitly programmed for the task.
OBJECTIVE OF THE INVENTION
SCOPE: The scope of the no-ball detection and predictions include robust software for both AI and embedded systems, buzzers for no-ball detection, an app for reviewing the no-ball decision, backup hardware in the case of equipment failure, failure detection alerts. The project aims to ensure safety, functionality, and regulatory compliance for mass production.
OBJECTIVE: The objective is to develop a no-ball detection and prediction for domestic cricket grounds in India with AI and embedded systems integration for no-ball detection, an app for reviewing the no-ball decision, buzzers for detection, backup hardware in the case of equipment failure, failure detection alerts. The project aims for safety, functionality, and regulatory compliance.


SUMMARY OF THE INVENTION
LAXMANA-REKHA MAPAKA is powered by AI based embedded systems, offers a comprehensive solution for no-ball detection and prediction in domestic pitches. It seamlessly integrates a range of sophisticated functions. First is the array of infrared (IR) sensors that detect the no ball. Second is the backup ultrasound sensor. Third is the camera sensor that both detects as well as predicts the no-ball occurrence. The raspberry-pi module is the master, and is responsible for all the functions that take place. We have bio-mimicked the spinal cord in the human body. The actuation of the "sensor safety box", is similar to that of the human spine during reflex actions. Here the actuations are controlled by the Arduino nano, as well as Arduino uno. When a no-ball occurrence is predicted, the buzzers set off, which indicated that the no-ball has occurred. Additionally, Dharmaraya can be used by the umpire if the player asks for a review. Together these features make sures that false decisions on no-balls aren't made, as these rely on cutting edge AI based embedded systems.











DETAILED DESCRIPTION OF THE INVENTION
LAXMANA-REKHA MAPAKA involves the creation of an innovative model for domestic cricket grounds. Integrated with multiple sensors, AI, the model offers features to reduce the false decisions being taken by the umpires during domestic matches. These features include active no-ball detection, no-ball prediction, photographic evidence of no-ball, buzzer during the time of no-ball occurrence, kavach. The kavach also called as "sensor safety box", is used to protect the embedded boards, from high-speed balls, maintain level playing surface, while running between the fields. The raspberry pi makes sures to reduce the false no-balls decision. In the case of any player review, the umpire can easily see the photographic evidence of the no-ball occurrence through Dharmaraya. To make sure that no-ball is signalled on time, the piezo buzzer alerts the umpire that the no-ball has occurred. The LAXMANA-REKHA MAPAKA project spans the entire development life cycle, starting with initial design and development, followed by rigorous testing and fine-tuning for optimal performance. The primary objective is to significantly reduce the occurrence of false no-ball decisions in domestic cricket matches. This initiative places a strong emphasis on ensuring the technology is not only highly functional and reliable but also adheres to regulatory standards to facilitate mass production. Through careful design and precise implementation, the project aims to revolutionize grassroots cricket by introducing accurate and dependable no-ball detection technology for use on domestic pitches.





CLAIMS
We claim,
1. The module combines infrared (IR) sensors, ultrasonic sensors, and a camera to accurately detect and predict no-ball events on domestic cricket grounds.
2. The system includes a piezo buzzer that provides immediate audio alerts upon detecting a no-ball, ensuring timely notification to umpires and reducing their decision-making pressure.
3. The system employs a network of embedded controllers that communicate efficiently with various sensors, enabling rapid and reliable no-ball detection and prediction.
4. The AI module processes data from the sensors to perform real-time analysis and prediction of no-ball occurrences, ensuring high accuracy and minimizing false decisions.


, C , C , Claims:1. The module combines infrared (IR) sensors, ultrasonic sensors, and a camera to accurately detect and predict no-ball events on domestic cricket grounds.
2. The system includes a piezo buzzer that provides immediate audio alerts upon detecting a no-ball, ensuring timely notification to umpires and reducing their decision-making pressure.
3. The system employs a network of embedded controllers that communicate efficiently with various sensors, enabling rapid and reliable no-ball detection and prediction.
4. The AI module processes data from the sensors to perform real-time analysis and prediction of no-ball occurrences, ensuring high accuracy and minimizing false decisions.

Documents