The project was developed to assist visually impaired people in outdoor navigation by giving them information about objects in the close vicinity. Developed a prototype that recognised an object and its relative distance from the user which was then spoken to the user using the user’s smartphone. Involved navigation using Google Maps API to find the shortest route for the visually impaired person to the destination. Used the transfer learning concept to learn the specific objects found in the outdoor environment using the Inception Model. Used stereo camera to measure the distance of the object from the user. All this was mounted on a Raspberry Pi which transferred the information about surroundings to the user’s smartphone which spoke out the information using the speaker.

The project was developed to assist visually impaired people in outdoor navigation by giving them information about objects in the close vicinity. Developed a prototype that recognised an object and its relative distance from the user which was then spoken to the user using the user’s smartphone. Involved navigation using Google Maps API to find the shortest route for the visually impaired person to the destination. Used the transfer learning concept to learn the specific objects found in the outdoor environment using the Inception Model. Used stereo camera to measure the distance of the object from the user. All this was mounted on a Raspberry Pi which transferred the information about surroundings to the user’s smartphone which spoke out the information using the speaker.

The project aims at making the human life simpler and more comfortable but also keeping a check on the energy consumption by various home appliances. Detected the presence of person or people in the room, compute the number of people in the room, analyse the state of the people/person in the room, i.e., sleeping, talking in a meeting, resting using the computer vision from which we will turn off the home appliances, if no presence is detected. Monitor the home appliances according the presence and state of the people/person. The use of computer vision instead of traditional sensor network-based approach is because computer vision overcomes the limitations of the sensor networks in the given domain effectively. This project not only deals with the real-life problem of energy consumption by home appliances but also tries to make human lifestyle comfortable by fully automating the appliances use without any physical intervention.

This project focused on designing a system based on fuzzy logic with a set of input and output parameters to obtain an optimised solution. A comparative analysis was carried out among various types of membership functions of input and output on Mamdani Fuzzy Inference System and Sugeno Fuzzy Inference System. The proposed approach is applicable to design a better system model for a given set of rules. Compared Mamdani and Sugeno FIS for 13 input parameters and 6 output parameters for different input Membership Functions and output membership functions. Also, mathematically proved the correlation between the different FISs and concluded with 9 inferences.

Leave management system which was a part of NIT Raipur’s Vigyaan Exhibition Model was extended to include more functionalities on the mobile application and the Database was normalized to remove redundancies and anomalies. While the focus was on Front End during NIT exhibition, more focus on the back end was put in during the course project. E-R diagram and Use-Case diagram were also designed before the extension was implemented. 

Hardware computations are much faster than their software counterparts due to minimum overhead. Software approaches to the computations generally encounter the various type of delays and overheads which results in a larger computation time. Therefore to minimise the computation time, we need to implement in the hardware itself. In this project, we implemented different techniques of edge detection namely Sobel, Laplacian, and Canny and color selection. We first implemented Sobel, Laplacian, and Canny edge detection algorithms in software and after comparative analysis, Sobel edge detection technique was implemented on Altera DE2 FPGA.

Hello IIITNR is a Mobile Application for Android smartphones for the members of IIITNR with features like Details of faculty, administrative staff and students with a game and a section dedicated for latest events, notices and achievements of students and a salary receipt page for faculty and administrative staff

Leave management system was a part of NIT Raipur’s Vigyaan Exhibition Model. It is a system comprising of a website and a mobile app to digitalize the classical way of leave-taking in an institute. It used HTML5, CSS3, JSS as front-end languages for website and Django Framework as backend whereas for Mobile App, it used Java, C#, and XML as front end and LMS used SQL for DBMS. 

An Arduino based project which was a part of the evaluation in the second semester. The project uses the simple concept of OHM’s Law where a low DC voltage is applied at the feeder end through a series resistor. The current would vary depending upon the length of the fault of the cable. The series resistor voltage drops changes accordingly which is then fed to the analog input of the microcontroller. The project is assembled with a set of resistors and a set of switches.