T.A.R.S is a quadruped that can walk at any terrain. The main aim of the project is to leverage this technology in botanical gardens so as to monitor plant health. The other application of it being monitoring condition of the crop. T.A.R.S uses unique creep gait. It is specially programmed to mimic human and spider movement simultaneously. The program being quite small is written to have tars move over 500 steps at one Command.

VISU(VIT-AP Intelligent super Utility) is a 3D printed robot built from scratch using minimal design and simple yet sophisticated electronics. Backed by Arduino and Raspberry pi and customized so as to make it modular in terms of design and technology that expands its range of abilities. The robot comes equipped with Voice and Face recognition tech. The arms and torso are powered by high torque Servo motors that provide enough power to lift a baby. Powered by over 25 motors, the robot can effortlessly mimic human movement. Every piece of tech involved has been hacked, modified and customized to satisfy constraints that were once a limitation. This research published in IEEE Consumer Electronics (Impact Factor: 4.01)

Vinci X is a body vital monitoring garment that records body vitals and sends them to cloud and app where Machine Learning algorithms analyze the data and provide user with a detailed report both in real-time and post-workout. Users can in real-time check their individual muscle activity and ECG along with other vitals. A visualization shows, graphically, the exerted muscle force and areas to work on. The same report can be sent to a trainer or a physician and seek help.The garment has embedded sensors in it.All the sensor values are transmitted to app and cloud with a cellular based ARC that powers the suit and is detachable. Customers can use this garment to help them with working on weak areas and increase workout efficiency by 65%. This research published in IEEE Transactions on Consumer Electronics.

Over 60% of people around the globe consume Alcohol and Cigars daily. Many intake them beyond the permitted limit causing disease such as lung cancer, Liver and kidney Failure. Chain-smokers and Alcoholics do not have a metric or system that monitors their intake level and alerts the user in case of excess consumption. To help users monitor their consumption, we introduce Cleo Eyeglasses in this research. Cleo is a wearable spectacles with mounted camera and single board computer that performs custom trained object recognition to identify alcoholic beverages and cigarettes. Upon recognition, a log is automatically maintained in the corresponding mobile application. The user can set the limit or threshold on consumption levels. If the system detects consumption level beyond the permitted threshold, an alert is sent to the prescribed medical official for assistance.

The project Cerebro is the Mind controlled wheelchair which controls the direction and motion based on the decision taken by the user. The mindwave headset is used in the mindcontrolled wheelchair to pick up EEG signals from the brain. These signals are processed by a microcontroller which in turn takes a decision regarding the motion and direction of wheelchair and accordingly drives the motor.

Vitapian is a chatbot used by VIT AP to answer its most common and general queries. Vitapian lets you know about the teachers, their cabin numbers along with the intercom details and other miscellaneous.

In the world of operating systems linux leads the biggest market share from embedded IoT devices to super computers.There are plenty of flavours (linux versions) for each use case, but we are yet to have an OS tailored for AI developers. We bring you the OhYes OS an OS tailored for AI developers ranging from ninjas to babies. This is custom build operating system developed by our second year student.

The aim of this project is to censor the obscene and indecent images on a website. It is a plugin developed for accomplishing the same using neural networks. Once the extension is installed, all the images on a website accessed by the user will be processed and based on the extent of nudity depicted, images will be removed on the client side.

What could possibly be the intention behind knowing the number of trees in an area? Be it Disaster Management, calculating the assets of the state, or under advanced circumstances, the ability to detect the quality of the trees, the Coconut Detection System is one to look into. Using image processing to detect coconut trees from aerial views, is an innovative design which requires object detection models. During the development of the project, the members also developed a new object detection model – RetinaNet model. A combination of Focal Loss and ResNet, this new model surpassed the R-CNN model, while still being a stage one detector. The final results of the project were accurate to a point where it could be deployed on a drone and be applied on live-feed. There is also further scope to better the model. This is a collaborative work with APSAC. This paper is submitted to Journal of Scientific and Industrial Research.

Project Dante is an e-bike that is equipped with state of the art object detection and integrated with application controlled features. Mechanically, the vehicle can travel over 80 Kms in one single charge.

With technology developing, the health sector has been developing too. ReMedic is yet another step towards faster medical treatment to accident victims. It is an emergency service and aims at shortening the time by incorporating new-age technologies like drones and health monitoring sensors. In case of an accident, the UID and GPS Coordinates call for the nearest hospital’s assistance by sending live data and feed using ML Algorithms. The case is then assigned to the available doctor. Machine Learning is used to analyse the patient’s condition and suggest solutions to the doctor. Medication is loaded into drones and sent to the accident site for initial treatment while the ambulance is sent to pick the victim up. ReMedic aims at redefining and improving the emergency services and save lives

Nirvana is a Retail product classification checkout unit that use state-of-the-art computer vision to identify products as you drop them in the cart. Also, remove the product from the invoice that is removed from the cart. All by just using AI. Nirvana helps you in skipping checkout lines with ease and doesn’t waste your time and energy on waiting in checkout lines. Scan and Go is the future.

VIT-AP Whatsapp chatbot allows students to retrieve their timetable, class timings, announcements made on Vtop by simply just asking the bot. The bot leverages state-of-the-art NLP to recognise your simple commands and fetches data from the DB. Therefore, giving the student On-the-go updates

Furniture Land is an Augmented Reality Application that can be linked with any online furniture marketplace, bringing in the products in virtual reality to allow customers pre-plans the furniture locations at home. The application also allows user to purchase and place an order from the cart option in the app

Security in web services is not well defined and is largely based on measures employed by the organization providing the service, the effectiveness of which vary greatly depending on the expertise, implementation, and business motivation. To address the mentioned issue, this research proposes an open standard called Decentralized Open Web Cryptographic Standard (DOWCS) and reference implementation for decentralized protection of sensitive data. Services may adhere to the standards, to assure security to the end-user. Taking OAuth and PGP as reference models, the standard incorporates multiple layers of security to ensure secrecy of the said data while also decentralizing the key information required to derive the confidential data from the encrypted format.

SimplyMime is a wholesome gesture recognition system to make life simpler. It combines the power of Artificial Intelligence of Things (AIoT) to provide a better and faster user experience in the ubiquitous environment just with the movement of the fingers. The user can control the systems in the integrated ubiquitous environment just by moving the hands in the air and making gestures just like we have seen in the movies. A lot of day-to-day activities like moving the mouse, controlling volume, drawing, opening specific applications, home automations etc., can be much simpler with our SimplyMime. SimplyMime not only makes this a reality but also follows the user around their room so that every gesture the user makes is clearly read, and the task is accomplished. The system would track the user movements and a webcam mounted on to a microcontroller would turn to the user wherever the user is in the room. The user can further make relevant gestures with their hands and the system will immediately respond. SimplyMime uses face detection, pose estimation combined with port communication to the microcontroller to achieve this. This system can be further scaled and used for various other purposes like gaming, Unmanned vehicle control (e.g.: drones) and other controls etc.

The rise of global temperatures, over the past few decades, has disrupted the usual balance of nature. As a result of increasing temperatures, wildfires have destroyed millions of acres of land, thousands of structures, and homes. The pollution and toxic gases produced by the wildfires are carried out to thousands of miles, thus threatening the lives all around the world. Most wildfires occur due to anthropogenic factors, which cannot be predicted solely based on climate conditions. Henceforth, to detect wildfires before escalating, we propose iDrone, which is a wildfire detection system equipped with an end-to-end CNN image classification model: XtinguishNet, trained on a wildfire imagery dataset to detect the possible flames or smokes in an image. In addition, our approach also acquires the weather data and the intensity of the fire. Contrasting with existing wildfire detection systems, our proposed solution is a fusion of the Internet of Things (IoT) and Deep Learning, aiming to provide a one-stop solution for all the needs required to minimize the damage caused by wildfires. When validated and tested using various benchmark datasets, video surveillance, iDrone acquired a high accuracy of 98.36% with the least computational power.

Voice assistants like Siri, Google Assistant, Alexa etc. are used widely across the globe for home automation, these require the use of special phrases also known as hotwords to wake it up and perform an action like “Hey Alexa!”, “Ok Google” and “Hey Siri” etc. These hotwords are detected with lightweight real-time engines whose purpose is to detect the hotwords uttered by the user. This research presents the design and implementation of a hotword detection engine based on one-shot learning which detects the hotword uttered by the user in real-time with just one or few training samples of the hotword. This approach is efficient when compared to existing implementations because the process of adding a new hotword in the existing systems requires enormous amounts of positive and negative training samples and the model needs to retrain for every hotword. This makes the existing implementations inefficient in terms of computation and cost. The architecture proposed in this research has achieved an accuracy of 96.8%.