Field of Invention
Cricket is a globally famous sport in which various technologies are employed to assist match umpires in making judgments. The decision of whether a bowled delivery is a no-ball or a legal ball is frequently disputed owing to human perception. Because a single ball may decide the game's outcome, it's clear to make the best option possible while there's no ball. To identify the change in pixel values, we separated the bowling crease into two sections and used the image subtraction approach on both regions in this work. After that, we tested our approach on real-world video frames. Because our approach for detecting the overstep no ball is based on pixel-by-pixel picture subtraction. Cricket is a bat-and-ball sport in which a single delivery may change a predicted winner into a loss. As a result, each delivery is seen as a critical time for both sides. Umpires are in charge of judging whether a ball bowled by a bowler is approved in every cricket match. When umpires rule against a delivery, it can happen in a variety of ways. Some, instances have been designated as No Ball. For unlawful conduct by bowlers or fielders, a No Ball might be declared. The opposing side receives an additional run and delivery as a result of a No Ball. Furthermore, batsmen will not get dismissed unless they are run out.

Background of Invention
One of the most prevalent causes is the front foot overstepping the popping crease when throwing the ball. However, in certain circumstances, utilising television replay, examining this type of No Ball takes a few minutes. As a result, umpires make decisions based on their perceptions. However, human perception is not always correct. Furthermore, due to the limits of current technology, it is not always feasible to get an accurate conclusion. In that instance, the batting side gets the benefit of the doubt. As a result, spectators and cricket fans are left in a state of uncertainty and dispute. To boost the acceptance of the judgments, it is vital to eliminate dispute. If this can be accomplished by technological means, the game will be more fair and pleasant. However, developing technologies that can determine the overstepping No Ball in real time and with more precision is difficult. Previously suggested investigations in this subject have attempted to answer the problem, however due to the use of sensors on the field and bowlers, they are infeasible, pricey, and prone to mistake.

Object of Invention
1. AI Processor
2. Power Supply
3. Laser Distant Sensor
■4. Bluetooth 5.0

Summary of Invention
On the other hand, in this study invention, we present a computer vision-based technique that does delicate pixel-based distance analysis between the feet and the popping crease, resulting in a high degree of choice accuracy. Because it would get video feed from broadcasting cameras, the suggested solution does not require any additional infrastructure. Due to the lack of an infield sensor and other devices, our suggested technique is projected to perform better and be less expensive to operate. Cricket is one of the most widely played sports in the world. Different technologies are utilised in cricket matches to assist match umpires in making judgments. Disputes arise frequently because of human perceptions of whether a bowled delivery is a no-ball or a legal ball. Because a single ball may decide the outcome of the match, it's apparent to make the best option possible when it.comes to no ball. We employed image subtraction method in existing approach to identify foot overstep no ball in cricket match, which does not contain sensors in cricket field. As a result, players will not be distracted.
We employ Metal in the Bowler's shoe (customised in the heal portion) to detect the Front Foot No-Ball when the Bowler bowls the Overstepped Delivery in the proposed task. It indicates that the front foot has crossed the Popping crease. The proximity sensor in this system detects overstepping deliveries and sends an alarm message to the umpire, who then signals it as a No-Ball. The goal of the game is for one team to score more runs than the other. There are two innings in a cricket match. Before the competition begins, both captains are requested to toss the ball. Following the toss, the batting team has two batsmen and the bowling team has eleven players on the field. In cricket, certain techniques are utilised to determine run outs and edge detections, but one of the major issues has been detecting the front foot 'No-ball,' which has gone unreported in recent matches. On-field umpires have a lot on their plates, including something as complicated as field location. Various technologies are being employed to assist match umpires in making decisions. Determining whether a bowled delivery is a no-ball or legal ball is frequently disputed owing to human perception.
Anyone who follows sports like cricket understands the importance of the umpire's judgement. A bad judgement in a game's vital moments causes an injustice to a team; it has the same impact of winning or losing the game; the game is spoilt, which is a huge disappointment to the supporters. The primary aspects of the game are turned into activities by sports science, such as practise before, during, and after competition.

Detailed Description of Invention
In this invention of prototype device, when the power supply is given through the battery the device starts functioning. The battery is connected to the Jetson Nano AI Processor. The power of modern AI is now available for makers, learners, and embedded developers everywhere.
NVIDIA® Jetson Nano™ Developer Kit is a small, powerful computer that lets you run multiple neural networks in parallel for applications like image classification, object detection, segmentation, and speech processing. All in an easy-to-use platform that runs in as little as 5 watts.
It's simpler than ever to get started! Just insert a microSD card with the system image, boot the developer kit, and begin using the same NVIDIA Jet Pack SDK used across the entire NVIDIA Jetson™ family of products. Jet Pack is compatible with NVIDIA's world-leading AI platform for training and deploying AI software, reducing complexity and effort for developers.
Jetson Nano is supported by NVIDIA Jet Pack™ with the same CUDA-X™ software stack used for breakthrough Al-based products across all industries. Jet Pack includes the latest NVIDIA tools for application development and optimization and supports cloud-native technologies like containerization and orchestration for simplified development and updates.
Proven frameworks built on top of Jet Pack give Jetson developers greater performance and scalability as they create industry-specific end products. These include NVIDIA Deep Stream and Transfer Learning Toolkit for intelligent video analytics, NVIDIA Clara™ for healthcare imaging, genomics, and patient monitoring, and NVIDIA Isaac™ for robotics. Opto NCDT sensors have set milestones for industrial laser displacement measurement. Whether for displacement, distance or thickness measurement, Micro-Epsilon laser sensors are considered one of the best in their class. These laser sensors are used e.g. in measurement and monitoring tasks in factory automation, electronics production, robotics and vehicle construction. Due to high measuring rate, laser sensors from Micro-Epsilon offer high measurement accuracy and provide reliable results even in continuous industrial operation.
Most of the opto NCDT sensors can be set up using a web interface. Therefore, set up and configuration of the sensors is convenient and can be stored and transferred to other

sensors via a standard web browser. The opto NCDT BL models are equipped with a blue laser diode and are used when standard sensors with a red laser diode are operating at their performance limits. Due to its shorter wavelength, the blue laser does not penetrate the target surface, projecting a small light spot on the surface and therefore providing stable and precise results. This technology is preferably used with organic and (semi-)transparent objects, as well as for red-hot glowing metals.
Measurement tasks involving blue laser sensors on red-hot glowing objects exceeding 700 °C and transparent objects such as glass and plastics, are protected by patent law. The opto batt NCDT Blue Laser models achieve excellent signal stability and thus precise measurement results on these surfaces.
Bluetooth 5 is the most significant advancement in the Bluetooth standard since the introduction of Bluetooth Low Energy in Bluetooth 4.0. It is taking Bluetooth LE to the next level and is making brand new use cases possible and improving existing ones.
There are four significant new features of Bluetooth 5:
• A higher bit rate of 2 Mbps.
• A long-range mode with better sensitivity at two new lower bit rates of 500 kbps and 125 kbps.
• An 8-x improvement in broadcast capability with advertising extensions.
• An improved channel selection algorithm (CSA #2) which enables improved .channel coordination and coexistence efficiency with other Bluetooth and non-Bluetooth traffic.
The nRF52 Series multiprotocol SoCs are high performance that support Bluetooth 5. The nRF52840 supports all new features of Bluetooth 5, whilst the other members support all Bluetooth 5 features with the exception of the long-range modes. The nRF52 Series family of devices cover baseline through general purpose up to highly sophisticated Bluetooth 5 . devices. All devices in the family are supported by qualified, high performance, production-grade software stacks. Together they offer an unparalleled development option for creating products with Bluetooth 5.

Detailed Description of Drawings
(1) Figure (i) shows the Block Diagram
(2) Figure (ii) shows the Laser Distant Sensor
Op to NCDT sensors has set milestones for industrial laser displacement measurement. Whether for displacement, distance or thickness measurement, Micro-Epsilon laser sensors are considered one of the best in their class. These laser sensors are used e.g. in measurement and monitoring tasks in factory automation, electronics production, robotics and vehicle construction. Due to high measuring rate, laser sensors from Micro-Epsilon offer high measurement accuracy and provide reliable results even in continuous industrial operation. Most of the op to NCDT sensors can be set up using a web interface. Therefore, set up and configuration of the sensors is convenient and can be stored and transferred to other sensors via a standard web browser.
The op to NCDT BL models are equipped with a blue laser diode and are used when standard sensors with a red laser diode are operating at their performance limits. Due to its shorter wavelength, the blue laser does not penetrate the target surface, projecting a small light spot on the surface and therefore providing stable and precise results. This technology is preferably used with organic and (semi-)transparent objects, as well as for red-hot glowing metals..
Measurement tasks involving blue laser sensors on red-hot glowing objects exceeding 700 °C and transparent objects such as glass and plastics are protected by patent law. The op to NCDT Blue Laser models achieve excellent signal stability and thus precise measurement results on these surfaces.
(3) Figure (iii) shows the JETSON Nano AI Processor
The power of modern AI is now available for makers, learners, and embedded developers everywhere.
NVIDIA® Jetson Nano™ Developer Kit is a small, powerful computer that lets you run multiple neural networks in parallel for applications like image classification, object detection, segmentation, and speech processing. All in an easy-to-use platform that runs in as little as 5 watts.

t's simpler than ever to get started! Just insert a micro SD card with the system image, boot :he developer kit, and begin using the same NVIDIA Jet Pack SDK used across the entire AVIDIA Jetson™ family of products. Jet Pack is compatible "with NVIDIA's world-leading <\I platform for training and deploying AI software, reducing complexity and effort for developers.
Jetson Nano is supported by NVIDIA Jet Pack™ with the same CUDA-X™ software stack used for breakthrough Al-based products across all industries. Jet Pack includes the latest NVIDIA tools for application development and optimization and supports cloud-native technologies like containerization and orchestration for simplified development and updates.
Proven frameworks built on top of Jet Pack give Jetson developers greater performance and scalability as they create industry-specific end products. These include NVIDIA Deep Stream and Transfer Learning Toolkit for intelligent video analytics, NVIDIA Clara™ for healthcare imaging, genomics, and patient monitoring, and NVIDIA Isaac™ for robotics.
(4) Figure (iv) shows the Bluetooth 5.0
Bluetooth 5 is the most significant advancement in the Bluetooth standard since the introduction of Bluetooth Low Energy in Bluetooth 4.0. It is taking Bluetooth LE to the next level and is making brand new use cases possible and improving existing ones. There are four significant new features of Bluetooth 5:
• A higher bit rate of 2 Mbps.
• A long range mode with better sensitivity at two new lower bit rates of 500 kbps and 125 kbps.
• An 8 x improvement in broadcast capability with advertising extensions.
• An improved channel selection algorithm (CSA #2) which enables improved .channel coordination and coexistence efficiency with other Bluetooth and non-Bluetooth traffic.
ThenRF52 Series multi protocol SoC'sare high performance that support Bluetooth 5. The nRF52840 supports all new features of Bluetooth 5, whilst the other members support all Bluetooth 5 features with the exception of the long range modes. The nRF52 Series family of devices cover baseline through general purpose up to highly sophisticated Bluetooth 5 devices. All devices in the family are supported by qualified,

high performance, production-grade software stacks. Together they offer an unparalleled development option for creating products with Bluetooth 5.

Different Embodiment of Invention
i. This system explains how sensors may play an important part in sports as well. Here, we employ sensors in the ground to identify the front foot no ball, which lowers the labour and controversy for umpires.
ii. The sensors on the popping crease instantly identify the No Ball. This eliminates the involvement of the On-Field Umpire and the Third Umpire in the No Ball judgement.
iii. By resolving this issue, cricket will be able to achieve 100% accuracy in no-ball situations without the need for human intervention.
iv. The above-mentioned performance is also visible on the mobile app.
v. Coaches can have a detailed understanding of a batsman's strengths and flaws.
vi. It. therefore allows coaches to effectively communicate their opinions to the batter in order to enhance the area of weakness.

Application of Invention
a. To begin, we created a template frame for each of the cameras, where the marker of
popping crease is recognised using the Hough transformation method.
b. Then, using image subtraction analogies, we applied it to the video frames and
template frame from the umpire's chosen camera.
c. Our suggested solution has eliminated the inability of human vision to determine
whether or not a ball was overstepped on a wiped-out popping crease.
d. Our technique, to the best of our knowledge and based on multiple no ball detection
approaches and their application, can be successful and efficient.

We Claim
The invention of AI Based No Ball Detection System in Cricket Field comprises of:
1. In order to identify foot, overstep without a ball in a cricket match, we employed an image subtraction method that does not need sensors on the cricket field.
2. As a result, there will be no distractions for the athletes. This concept may be used to various types of no ball detection, such as foot and crease detection and wide ball detection.
3. Our specific goal is to create an automated cricket umpiring system based on computer vision.
4. The suggested approach has aided in making precise judgments at vital points in the game.
5. It raises the spirit of the game by introducing new tools that, with advancements in technology, may be used to address future issues such as monitoring the ball in real-time, recognising the absence of a ball, and so on.
6. It is possible to address the accuracy and in-time identification of faults in outdoor sports, which is also a major challenge for researchers.