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Working IoT, AI/ML and embedded builds with abstracts, component lists, documentation, and developer support — ready for your final-year submission.
smart agri with wild life and solenoid and npk sensor
Modern agriculture demands smart, scalable, and autonomous solutions to tackle challenges such as crop disease, wildlife intrusion, and inefficient irrigation. This project presents a Smart Agriculture System integrating IoT and Machine Learning (ML) to monitor environmental conditions, detect leaf diseases, and deter wildlife in real time. At the core, an ESP32 microcontroller collects data from a temperature sensor, soil moisture sensor, water level sensor, and other components. A solenoid valve, controlled through a relay, along with a water pump, automates irrigation based on soil conditions. For plant health, an ESP32-CAM, interfaced via a camera converter, captures leaf images which are processed using ML algorithms through a Flask-based web server to identify signs of disease. Wildlife detection is achieved through real-time video analysis, triggering a buzzer, LED light, or servo motor-based deterrent system to scare animals away. A toy-based setup with a container simulates the real-time farm environment, while an external adaptor powers the system for stability. The dashboard offers real-time monitoring, historical logs, and remote actuation features. This solution promotes precision agriculture, resource optimization, and crop protection through intelligent automation.
Smart Knee Brace Enhancing ACL Rehabilitation with Integrated Sensor Tech
Anterior Cruciate Ligament (ACL) injuries are among the most common and serious knee injuries, especially among athletes and physically active individuals. The rehabilitation process after ACL reconstruction is long and requires precise monitoring of knee movements to ensure proper recovery and prevent re-injury. Traditional rehabilitation methods often rely on subjective feedback and periodic clinical assessments, leading to potential inconsistencies and lack of continuous monitoring. This project presents a Smart Knee Brace system that integrates advanced sensor technologies with an ESP32 microcontroller to support real-time monitoring and intelligent feedback during ACL rehabilitation. The system is equipped with flex sensors to measure knee flexion angles, force-sensitive resistors (FSRs) to assess weight distribution and pressure during exercises, and an MPU6050 IMU sensor to track joint motion and orientation in three dimensions. All sensor data is processed and transmitted wirelessly via Bluetooth or Wi-Fi to a custom mobile application, enabling users and physiotherapists to track progress, detect abnormal movement patterns, and receive instant feedback. The system also includes optional haptic feedback (via vibration motor) and visual alerts (OLED display or mobile app) to notify the user in case of incorrect motion or overexertion. The entire device is embedded into a soft, ergonomic knee brace to ensure comfort and usability during physical therapy sessions. By combining wearable technology, wireless communication, and smart sensing, this project offers a cost-effective, portable, and data-driven solution for personalized ACL rehabilitation. It enables continuous assessment, improves patient engagement, and empowers clinicians with actionable insights, ultimately leading to faster recovery and reduced re-injury risks.
WOMEN Safety with Cam and gps and gsm
Ensuring women's safety in real-time situations such as harassment, assault, or medical emergencies is a growing societal need. Traditional mobile applications or manual alert systems are often ineffective during extreme stress or panic, where the victim may be unable to operate a smartphone. To address this challenge, this paper presents the design and implementation of a smart, wearable, IoT-enabled safety device that autonomously monitors vital signs and detects emergency situations based on sudden physiological changes or manual input. The system is powered by an ESP32 microcontroller integrated with a MAX30102 SpO₂ sensor to continuously monitor the user’s heart rate and blood oxygen levels. A sudden spike in heart rate, potentially caused by fear or physical stress, is identified as an emergency trigger. Alternatively, the user can press a panic button to manually activate the alert system. Upon detecting either condition, the ESP32-CAM module captures a real-time image of the surrounding environment. Simultaneously, the device acquires the user’s precise geographic location using a GPS module (GY-GPS6MV2). The gathered data—including live image, GPS coordinates, and alert message—is transmitted via the SIM800L GSM module using SMS to pre-configured emergency contacts such as family members or local authorities. To further enhance system usability and monitoring, a Flask-based web application is developed to facilitate remote access to sensor data and to integrate Twilio API for automated SMS communication. This system operates independently of internet access, making it ideal for remote or low-connectivity environments. The solution is compact, cost-effective, and designed for real-time, autonomous operation. It serves as a reliable technological intervention for enhancing personal safety and can be expanded for broader public safety applications.
water level monitoring system
Efficient water management is essential in both domestic and industrial applications to prevent overflow, water wastage, and dry-run damage to pumps. This project presents an IoT-based Water Level Monitoring System that continuously monitors the water level in storage tanks and automates the control of water pumps accordingly. The system is developed using a NodeMCU microcontroller, which interfaces with a water level sensor to measure the current level in real time. Based on predefined thresholds, the NodeMCU can activate or deactivate a water pump to maintain the desired water level. Data is sent to a Flask-based web interface, where users can remotely monitor tank levels and receive alerts if the tank is empty or full. This system offers a smart, low-cost, and scalable solution for water resource management in homes, agriculture, and commercial infrastructure.