Research/Project/Consultancy

STUDENT PROJECTS

1. SAMPATI - Smart Aerial Monitoring & Precise Advanced Target Identification is a drone project at JEC that aims to advance public safety technology, enhance crime prevention, and ensure secure data collection while protecting privacy. Utilizing a versatile drone fleet with advanced sensors, the project supports monitoring and inspections. A central command center with real-time analytics processes data, generates insights, and enables field communications. The technology stack includes a lightweight carbon fiber frame, an 11,000 rpm brushless DC motor, an STM32 flight controller, a 2200 mAh battery, and 2.4 GHz radio communications for over a 1.2 km range.

Team Members: Ichchhanshu Jain, Bharat Awasthi, Rigved Sharma, Ayush Gupta, Nitin Rai, Kartik Yadav, Atharva Talankar, Suryansh Bajpayi, Devanshu Mishra (Batch 2021-25)

2. Omnidirectional Gesture Control Robot—Introducing the Omnidirectional Gesture Control Robot, powered by ESP32 and Bluetooth signals. This versatile robot can move in all directions—forward, backward, left, right, diagonally, and even slide side to side without changing orientation. Controlled by operator gestures using a gyroscopic sensor, it offers seamless and intuitive navigation, making it ideal for various applications requiring precise and flexible movement.

Team Members: Abhi Jat (Batch 2021-25)

3. ScoutAI-IASR—The Industrial Autonomous Surveying Robot is an advanced autonomous system designed for industrial environments. Powered by a Raspberry Pi, it uses the Dijkstra algorithm for efficient pathfinding and navigation. Equipped with sensors for gas detection, temperature, and humidity monitoring, it also employs deep learning using two onboard cameras for rust detection. The robot features object and human detection for safety and delivers alerts via an onboard speaker. Real-time data is sent to a web control interface for remote monitoring and management. IASR enhances safety, reduces manual labor, and improves operational efficiency by automating industrial surveys and hazard detection.

Team Members: Princy Golhar, Aryan Rai (Batch 2021-25)

4. Gurren-T (Sumo Robot)—Designed and constructed a remote-controlled Sumo robot for competing in the Robo-Sumo Contest hosted by IIT Indore in 2024. This was a sub-3 kg robot with high-torque electric motors and a 6-phase radio-wave remote controller and L298 driver.

Team Members: Ayush Gupta, Atharva Talankar, Pratyush Sahu (Batch 2021-25), Sahil Rahangdale (Batch 2022-26)

5. Raahi- Raahi is a transformative application designed to enhance women's safety through innovative technology and thoughtful design. It offers tools and resources for confident navigation, blending discreet emergency features, educational materials, and user-friendly solutions. Whether for late-night commutes, solo travel, or everyday routines, Raahi empowers women to take control of their safety without compromising freedom or independence. Key features include SOS alerts, discreet panic buttons, background recording, fake calls, and check-in buttons.

Team Members: Ayush Nema, Sahil Gupta, Anshika Aneja, Sneha Chatterjee, Mufaddal Saba (Batch 2022-26)

6. Earth Leakage Monitoring & Alert System- The Earth Leakage Monitoring & Alert System is an innovative solution designed for continuous monitoring of earth leakage current and earthing continuity. Utilizing current & voltage sensors and a microcontroller with a ranged communication system, it provides 24/7 real-time data processing and dual alert systems for local (in audio & visual alert) and remote notifications (to maintenance staff). This system enhances public safety, reduces energy consumption, and ensures timely maintenance through predictive analytics, making it scalable and efficient for various environments.

Team Members: Ichchhanshu Jain, Bharat Awasthi, Rigved Sharma, Vivekanand Shah, Atharva Talankar(Batch 2021-25), Sahil Rahangdale(Batch 2022-26), Paridhi Jain(Batch 2023-27)

7. Automated Public Lighting System - This project implements an energy-efficient smart street lighting system using LDR and PIR sensors integrated with an Arduino microcontroller. The LDR sensor detects ambient light levels to activate streetlights at 45% intensity during nighttime. Upon detecting motion via the PIR sensor, the Arduino increases the light intensity to 100% for 5 minutes to ensure clear visibility. Additionally, two streetlights ahead illuminate to maximum brightness when motion is detected, enhancing safety for vehicles and pedestrians. This system optimizes energy consumption by maintaining low brightness in the absence of movement while improving visibility to reduce accidents in motion-dense areas.

Team Members: Kartik Yadav , Vivekanand Shah , Rigveda Sharma , Upendra Singh Rathore(Batch 2021-25) , Shratika Agrawal (Batch 2022-26)