ABSTRACT - Traditional waste management system operates based on daily schedule which is highly inefficientand costly. The existing recycle bin has also proved its ineffectiveness in the public as people do not recycle theirwaste properly. With the development of Internet of Things (IoT) and Artificial Intelligence (AI), the traditional waste management system can be replaced with smart sensors embedded into the system to perform real time monitoring and allow for better waste management. The aim of this research is to develop a smart waste management system using LoRa communication protocol and TensorFlow based deep learning model. LoRa sendsthe sensor data and Tensorflow performs real time object detection and classification.

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ABSTRACT - Since the beginning of the current COVID-19 pandemic, more than five million people have been infected and the numbers are still on the rise. Early symptom detection and proper hygienic standards are thus of utmost importance, especially in venues where people are in random or opportunistic contact with each other. To this end, automated systems with medical-grade body temperature measurement, hygienic compliance evaluation and individualized, person-to-person tracking, are essential, not only for disease spread intervention and prevention, but also to assure economic stability.Contact:
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ABSTRACT - The quantity of street mishaps increments and causes numerous issues. Numerous individuals bite the dust and harmed. Likewise, that causes numerous financial, social and mental issues that have negative effect on the improvement of the world. The primary reason for most of these mishaps is because of the infringement of the traffic rules: driving with high speeds, crossing a red-light signal, not keeping adequate separation with the front vehicle in the roadways, driving an inappropriate opposite way, and so forth. As the number of streets and avenues are huge and the all-out length of these streets is long, it is extremely unlikely to completely screen every one of them all the time by Traffic Patrol or camera frameworks. This paper proposes a framework to consequently and self-sufficiently identify and record the criminal traffic offenses without the help of the individual. Contact:
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ABSTRACT - : A self-driving car is a vehicle that senses its environment and navigates without human intervention and is a high research topic in computer vision that involves various sub- topics and need to be deeply reviewed. To accomplish this, our paper discusses hardware and software components of a self driving car that includes usage of technologies such as Deep learning techniques namely Convolution Neural Networks, YOLO algorithm, Hough Transform Algorithms, Transfer Learning, Canny Edge Detection algorithm. Software components such as Arduino IDE, Raspberry Pi Cam Interface, Open CV, Tensor Flow, Carla simulators and hardware components such as Raspberry Pi 3, Arduino UNO, Pi Camera, sensors like radar, lidar are used to build a prototype of a self- driving car. Contact:
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ABSTRACT - Agriculture is the pillar of the Indian economy and more than 50% of India’s population are dependent on agriculture for their survival. Variations in weather, climate, and other such environmental conditions have become a major risk for the healthy existence of agriculture. Machine learning (ML) plays a significant role as it has decision support tool for Crop Yield Prediction (CYP) including supporting decisions on what crops to grow and what to do during the growing season of the crops. The present research deals with a systematic review that extracts and synthesize the features used for CYP and furthermore, there are a variety of methods that were developed to analyze crop yield prediction using artificial intelligence techniques. The major limitations of the Neural Network are reduction in the relative error and decreased prediction efficiency of Crop Yield. Contact:
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ABSTRACT - Medicine distribution for the people in the remote tribal areas is finding tedious task for the Government’s, the Automatic medicine dispensing machine can aid to resolve the above mentioned requirement. This machine is equipped with some basic and emergency medication and can be refilled. It is a kind of computerized medicine storage system which can be easily accessed by the people in emergency without approaching any pharmacy this machine can be easy installed in the remote areas like long highways, desert areas, remote tribal areas and rural areas. Contact:
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ABSTRACT - The bridges get damaged due to aging or damage due to natural calamities, the people will remain unnoticed of it. Then the bridges will be a danger to travel as it can collapse anytime and leads to disaster. So, continuous bridge checking must be done for better bridge health. For solving this problem, a design for continuous bridge monitoring has been proposed using wireless IoT technology. This proposed design helps in monitoring bridges and can also be applied for flyovers. The design consists of monitoring devices as sensors like load sensor, water level sensor, vibration sensor and tilt sensor which are interfaced with communication devices. Contact:
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ABSTRACT - Annually, numerous cattle die of various diseases, necessitating the need for effective cattle health management. To ensure cattle disease detection at an early stage and identify the health status of cattle, we collected the environment temperature, humidity, illuminance, and infrared images of cattle in an actual-life environment as input parameters to develop an artificial intelligence characterization module for measuring deep body temperature in a contactless manner. By analyzing the correlation of estimating deep body temperature at the horn, eyeball, and nose of cattle, the most effective way of estimating this temperature was found to be at the horn. The estimation accuracy was particularly high in the sitting state. Contact:
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ABSTRACT - Around 43% of road accidents are due to drowsiness of a driver, says a study by the Central Road Research Institute (CRRI). Another leading cause for road accidents is drunken driving. Any amount of alcohol can impact a person’s driving ability and slows their response time. On an average 8 people die every day because of driving under the influence of alcohol. In case of an accident to reduce the fatalities and get quick emergency response a vehicle crash detection mechanism is necessary. Road accidents claim nearly three lives every minute, so it is of utmost importance to develop a cost efficient driver assistance system for automobiles. This will help us to monitor the driver’s physiological behaviours which will affect the stability of the vehicle and avoid accidents. To implement this, a variety of software algorithms, input and output extraction hardware tools have been employed in a collaborative way. Contact:
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ABSTRACT - The advancement in computer vision has assisted drivers in the form of automatic selfdriving cars etc. The misadventure is caused by driver's fatigue and drowsiness about 20%. It poses a serious problem for which several approaches were proposed. However, they are not suitable for real-time processing. The major challenges faced by these methods are robustness to handle variation in human face and lightning conditions. We aim to implement an intelligent processing system that can reduce road accidents drastically. This approach enables us to identify driver's face characteristics like eye closure percentage, eye-mouth aspect ratios, blink rate, yawning, head movement, etc. In this system, the driver is continuously monitored by using a webcam. Contact:
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ABSTRACT - The project proposes the idea of an image base added security for ATM machines using Raspberry pi that will eliminate the unauthorized usage of ATM cards by person other than the owner. The basic idea of the system is that after insertion of the ATM card into the machine and after the card verification, his image is captured using the webcam in the ATM and then it is matched with the card owner’s actual images already stored in the database. If the captured image matches with the stored images, it means he is the authorized user and moves to the next stage where he can enter the password to continue the transaction. When the stored image and the captured image don’t match, it means that he is an unauthorized user and thus blocking his access. The system may also inform the actual owner of the card regarding the card misuse. Contact:
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ABSTRACT - This paper shows the construction of a low-cost, open-source mechanical ventilator. The motivation for constructing this kind of ventilator comes from the worldwide shortage of mechanical ventilators for treating COVID-19 patients—the COVID-19 pandemic has been striking hard in some regions, especially the deprived ones. Constructing a low-cost, open-source mechanical ventilator aims to mitigate the effects of this shortage on those regions. The equipment documented here employs commercial spare parts only. This paper also shows a numerical method for monitoring the patients’ pulmonary condition. The method considers pressure measurements from the inspiratory limb and alerts clinicians in real-time whether the patient is under a healthy or unhealthy situation. Experiments carried out in the laboratory that had emulated healthy and unhealthy patients illustrate the potential benefits of the derived mechanical ventilator. Contact:
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ABSTRACT - We present some insights on the issue of crop destruction by wild animals. This is a serious concern for the affected farmers throughout the world and leads to significant social and financial distress among them. In order to understand the background of this problem, a survey of Katli village, Rupnagar, (India) was conducted. The main aim of the current work is to develop a device to protect crops from damage by wild animals by diverting them from the farms, without harming them physically. In this context, an Acoustic Repellent System has been designed which uses a convolutional neural network (CNN) based machine learning model and an IR camera to identify target animals, such as wild boar, nilgai, and deer. A Raspberry Pi (Rpi) module has been integrated with a camera and a frequency generator to recognise different animals and produce corresponding frequencies that keep them away from the farms of interest. Contact:
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ABSTRACT - Mining is one of the main activities in Andean Countries and occupational safety is one of the most important duties. Despite this, there has been an increase in the number of accidents, even the mortality rate is still high. Therefore, a Terrestrial Mobile Robot called “MineBot”, integrated with Tele operation Open-Source technologies, has been proposed for exploring and detecting chemical and physical as well as biological agents within the underground mines for the purpose of keeping safe the place for workers. Endowed with both a strong Mechanical design and an intuitive Telerobotic system applying User Experience design principles as well as Navigation Control, and Environmental Monitoring systems along with an Internet of Things (IoT) Platform storage. Contact:
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ABSTRACT - Reducing the number of road accidents in the current scenario is a very challenging societal problem. If the information regarding the accidents is given to the vehicles approaching the area, the secondary accidents can be considerably reduced. Vehicular Ad Hoc Networks (VANETs), the network of vehicles that can communicate with each other play a vital role in the reduction of such accidents. Many survey and research papers published on this topic majorly emphasize on implementation of VANETs using simulators but this research work is focused on implementation using hardware components.. Contact:
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ABSTRACT - Locating objects of daily use is a strenuous task for the visually impaired. The objective of this paper is to design a smart glove by using Deep Neural Networks (DNN) and object tracking algorithm which will guide the hand of the visually impaired to the desired object in an indoor environment. The smart glove has five micro-vibrating motors, each one used to guide the user’s hand in five different directions namely, forward, upward, downward, rightward and leftward. The palm of the glove has a Universal Serial Bus (USB) camera which feeds the real-time video to the Raspberry Pi for processing. The camera also has an inbuilt microphone. The user vocally commands the system to identify the desired object. The camera then detects the object using DNN. Contact:
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ABSTRACT - This paper presents a novel localisation method for electric vehicles (EVs) charging through wireless power transmission (WPT). With the proposed technique, the wireless charging system can self-determine the most efficient coil to transmit power at the EV’s position based on the sensors activated by its wheels. To ensure optimal charging, our approach involves measurement of the transfer efficiency of individual transmission coil to determine the most efficient one to be used. This not only improves the charging performance, but also minimises energy losses by autonomously activating only the coils with the highest transfer efficiencies. The results show that with the proposed system it is possible to detect the coil with maximum transmitting efficiency without the use of actual power transmission and comparison of the measured efficiency. Contact:
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ABSTRACT - The human communication is totally based on speech and text. So visually impaired people can gather information from voice. With the help of this project visually impaired people can read the text present in the captured image. In this Project we use Raspberry Pi Camera and this help to take pictures and that picture is converted into scan image for further process by using Image magick software. The output of Image magick software is in the form of scanned image this scan image is giving as an input to the Tesseract OCR (Optical Character Recognition) software to convert image into the text. For transformation of text into speech we use TTS (Text to Speech) engine. Experimental results shows that the analysis of different captured images and it will be more helpful to blind people. Contact:
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ABSTRACT - The sign language digits based on hand gestures have been utilized in various applications such as human-computer interaction, robotics, health and medical systems, health assistive technologies, automotive user interfaces, crisis management and disaster relief, entertainment, and contactless communication in smart devices. The color and depth cameras are commonly deployed for hand gesture recognition, but the robust classification of hand gestures under varying illumination is still a challenging task. This work presents the design and deployment of a complete end-toend edge computing system that can accurately provide the classification of hand gestures captured from thermal images. Contact:
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ABSTRACT - One of the important and vital roles in a country’s defense is played by the army soldiers. Every year Soldiers get strayed or injured and it is time consuming to do search and rescue operations. In this paper, we present a WSN-based environmental and health monitoring approach in which sensor data is processed using robust and stable algorithm implemented in controller. These processed data are then sent to the base station via low-cost, low- power and secure communication links provided by a LoRa network infrastructure instead of cellular networks, since, they are either absent or doesn’t allow data transmission in warzone or remote areas. We focus on monitoring environmental factors such as temperature, humidity, air pressure, air quality; physical factors such as motion, position, geographic location and health parameters like ECG (electro cardiograph), blood oxygen level, body temperature. Moreover, camera and microphone are used to monitor any undesirable situation of soldier. Contact:
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ABSTRACT - Because of the inaccessibility of Vehicle-to- Infrastructure correspondence in the present delivering frameworks, (TLD), Traffic Sign Detection and path identification are as yet thought to be a significant task in self- governing vehicles and Driver Assistance S ystems (DAS ) or Self Driving Car. For progressively exact outcome , businesses are moving to profound Neural Network Models Like Convolutional Neural Network (CNN) as opposed to Traditional models like HOG and so forth. Profound neural Network can remove and take in increasingly unadulterated highlights from the Raw RGB picture got from nature. In any case, profound neural systems like CNN have a highly complex calculation. Contact:
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ABSTRACT - Artificial intelligence in vision based approaches have proven to be effective in various phases of intelligent vehicle system (IVS). An IVS has to intelligently take many critical decisions in heterogeneous environment. Speed bump detection is one such issue in real world due to its varying appearance in dynamic scene. The major issue is the scaling appearance of such objects from far distance and often viewed as small entity. In the proposed article, deep learning and computer vision based speed bump detection model is proposed, which assist and control the driving behavior of an IVS before it reaches to speed bump. Contact:
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ABSTRACT - This paper presents a prototype of a smart robotic personal assistant vehicle based on Raspberry Pi and Zero-UI technology. Zero UI uses sensory experiences such as gestures, voice and movement to control the devices. A voice controlled robot vehicle implemented in this paper performs three functions, viz. movement of the robot is controlled using voice commands; it has the ability to articulate the text from a captured image using optical character recognition and present the equivalent audio to the user by using a built-in speaker or headset; it accepts voice commands from the user and uses Google Assistant API for any query processing and presents information searched on the Internet to the user in audio form using the built-in speaker or headset. Contact:
 +91-9008001602
 080-40969981

ABSTRACT - In our surrounding the Communication generally takes place through speech and text. The aim of this project is to provide an assistive technology to help the visually impaired person usage in disaster situations. The aim purpose of our paper is to develop a cap for blind which will guide them from their source to destination. The solution for smart Cap is to support visually Impaired person and it is cost effective wearable 'smart cap’. The Proposed system consists of web camera which is fitted into a cap, audio microphone, ultrasonic sensor, Raspberry pi, speaker for voice. The software’s use in this project is Image processing. open cv, numpy, python. Contact:
 +91-9008001602
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ABSTRACT - Blindness is a major problem in the society which made difficult for the person to lead his/her day-to-day life. The proposed system will detect, track and analyze the approaching objects and alert them to avoid collision. The PI camera and the Ultrasonic sensor sense the type and distance between the person and the object. The contactless temperature sensor senses the temperature of the object contactless manner using infrared rays. The GPS sensor tracks the route and location of the blind and the ESP8266 connects with the cloud for Realtime monitoring of the blind. Contact:
 +91-9008001602
 080-40969981

ABSTRACT - Reducing the number of road accidents in the current scenario is a very challenging societal problem. If the information regarding the accidents is given to the vehicles approaching the area, the secondary accidents can be considerably reduced. Vehicular Ad Hoc Networks (VANETs), the network of vehicles that can communicate with each other play a vital role in the reduction of such accidents. Many survey and research papers published on this topic majorly emphasize on implementation of VANETs using simulators but this research work is focused on implementation using hardware components. Henceforth, this research work proposes a real-time system with vehicular nodes that detects an accident and disseminates the message. Contact:
 +91-9008001602
 080-40969981