What is Reckoner that the LPU team has designed? There is so much buzz about it.

A team of LPU students and researchers under the guidance of Dr. Lovi Raj Gupta has proposed and designed an AI-based system, Reckoner, which will count the number of forge items and convey the data to the website where the owner can easily trace and monitor the no. Of forges prepared hourly, daily and even monthly. Reckoner is deployed in Victor Tools Pvt. Ltd. , Jalandhar where the team was finding difficulty in counting the number of forge items. The system utilizes DNN based to process the real-time data capture by the device and count the no. Of forges. Reckoner is an automated object counting system, comprising a camera configured to capture real-time images and/or videos of an industrial premise. The main computing unit is configured to receive the captured real-time images and/or videos from the camera located at a single node. It then divides the received videos into frames, drawing a static virtual line in the images and/or the frames of the videos. This further classifies objects present in the images and/or the frames of the videos by using a DNN model to detect a presence of an object, with a confidence value based on the classified objects by comparing the confidence value of the detected object with a predefined threshold value. The edge device monitors the Motion of the detected object when the confidence value of the detected object exceeds the pre-defined threshold value and increment count displayed on a counter display when the detected object crosses the drawn static virtual line.

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Reckoner is an automated object counting system, comprising a camera configured to capture real-time images and/or videos of an industrial premise. The main computing unit is configured to receive the captured real-time images and/or videos from the camera located at a single node. It then divides the received videos into frames, drawing a static virtual line in the images and/or the frames of the videos. This further classifies objects present in the images and/or the frames of the videos by using a DNN model to detect a presence of an object, with a confidence value based on the classified objects by comparing the confidence value of the detected object with a predefined threshold value. The edge device monitors the Motion of the detected object when the confidence value of the detected object exceeds the pre-defined threshold value and increment count displayed on a counter display when the detected object crosses the drawn static virtual line. An AI-based system, Reckoner, which will count the number of forge items and convey the data to the website where the owner can easily trace and monitor the no. Of forges prepared hourly, daily and even monthly.

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A team of LPU students and researchers under the guidance of Dr. Lovi Raj Gupta has proposed and designed an AI-based system, Reckoner, which will count the number of forge items and convey the data to the website where the owner can easily trace and monitor the number of forges prepared hourly, daily and even monthly. Reckoner is an automated object counting system, comprising a camera configured to capture real-time images and/or videos of an industrial premise. The main computing unit is configured to receive the captured real-time images and/or videos from the camera located at a single node. It then divides the received videos into frames, drawing a static virtual line in the images and/or the frames of the videos. This further classifies objects present in the images and/or the frames of the videos by using a DNN model to detect a presence of an object, with a confidence value based on the classified objects by comparing the confidence value of the detected object with a predefined threshold value. The edge device monitors the Motion of the detected object when the confidence value of the detected object exceeds the pre-defined threshold value and increment count displayed on a counter display when the detected object crosses the drawn static virtual line.

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Reckoner is an automatic object counting system that includes a camera set up to record live pictures and/or videos of a business location. The camera at a single node is configured to provide real-time photos and/or videos to the main computing unit. The received movies are then divided into frames by putting a static virtual line through the images or video frames. Using a DNN model to identify the existence of an item and a confidence value based on the classed objects, this further categorises the objects present in the images and/or frames of the videos by comparing the confidence value of the detected object with a predetermined threshold value. When the confidence value of the detected item exceeds the pre-defined threshold value, the edge device tracks the Motion of the object and displays an increment count on a counter display when the object passes the drawn static virtual line. A team of LPU students and researchers under the guidance of Dr. Lovi Raj Gupta has proposed and designed an AI-based system, Reckoner, which will count the number of forge items and convey the data to the website where the owner can easily trace and monitor the no. Of forges prepared hourly, daily and even monthly.

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Reckoner is an automated object counting system, comprising a camera configured to capture real-time images and/or videos of an industrial premise. The main computing unit is configured to receive the captured real-time images and/or videos from the camera located at a single node. It then divides the received videos into frames, drawing a static virtual line in the images and/or the frames of the videos. This further classifies objects present in the images and/or the frames of the videos by using a DNN model to detect a presence of an object, with a confidence value based on the classified objects by comparing the confidence value of the detected object with a predefined threshold value. The edge device monitors the Motion of the detected object when the confidence value of the detected object exceeds the pre-defined threshold value and increment count displayed on a counter display when the detected object crosses the drawn static virtual line. An AI-based system, Reckoner, which will count the number of forge items and convey the data to the website where the owner can easily trace and monitor the no. Of forges prepared hourly, daily and even monthly.

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Reckoner is an automatic object counting system that includes a camera set up to record live pictures and/or videos of a business location. The camera at a single node is configured to provide real-time photos and/or videos to the main computing unit. The received movies are then divided into frames by putting a static virtual line through the images or video frames. Using a DNN model to identify the existence of an item and a confidence value based on the classed objects, this further categorises the objects present in the images and/or frames of the videos by comparing the confidence value of the detected object with a predetermined threshold value. The edge device monitors the Motion of the detected object when the confidence value of the detected object exceeds the pre-defined threshold value and increment count displayed on a counter display when the detected object crosses the drawn static virtual line. An AI-based system, Reckoner, which will count the number of forge items and convey the data to the website where the owner can easily trace and monitor the no. Of forges prepared hourly, daily and even monthly.

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