Kenexoft's Smart Digital Monitoring Engine Enabled for Smart Retail, Smart Gated Communities, Smart Law Enforcement.

This project's major goal is to employ an AI-enabled SDME which is a real-time application (Framework). It is used to enable computers to execute executive functions such as decision-making, problem-solving, perception, and understanding human communication. We use AI to make a convolutional neural network (CNN), a python-based deep learning module that extracts streams, identifies, and processes images, and collects snapshots from videos before storing the data in the cloud. It has been developed in the existing AI-based Smart Identification Engine that can capture the Age, Gender of a particular person in real-time using an IP-enabled camera at malls and public places for advertisement and store that information in the cloud/physical storage (with real-time video analysis). Convolutional Neural Networks are a type of neural network that is mostly used for image classification, picture clustering, and object identification. Face recognition is one of CNN's key applications. Deep convolutional neural networks are preferred over other neural networks for achieving the highest accuracy. Convolutional Neural Networks (CNNs) are a form of feed-forward artificial neural network whose connection pattern is inspired by the visual cortex. In the proposed system, we use an IP enabled camera that can be linked by providing an Ip address; from this video source, we record the videos and, ideally, store the information of the videos in a Cloud/Physical storage by splitting the video into image, which is an output produced using AI techniques. AI enabled Smart Digital Monitoring Engine (SDME) is an effective implementation of AI’s convolutional Neural Network (CNN), a class of Deep Neural Networks to identify and process images and videos. AI enabled SDME framework can be used for various sectors and scenarios such as: A) Playing relevant Ads in Retail Malls based on the Gender/Avg. Age/Moods of the audience watching the LED screens playing the Ads. B) To automate the identification of Owners/ Tenants Vs Guests/Visitors in a Gated Community, through face recognition and vehicle no. recognition, and scalable for automation of gate/boom barrier opening/closing & more… Keywords: CNN (convolutional Neural Networks), Age and Gender Detection, OpenCV, TensorFlow, Tesseract.