The top and latest final-year projects for Electronics and Communication Engineering (ECE) in 2026 heavily focus on the convergence of embedded systems with advanced technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and Machine Learning (ML).
Here is a list of cutting-edge projects with their abstracts, categorized by their primary domain:
🤖 AI & Computer Vision Projects
1. AI-Powered Traffic Management System
Abstract:
This project proposes a Real-time Adaptive Traffic Management System using Computer Vision and a high-performance embedded platform like the Raspberry Pi or NVIDIA Jetson. The system utilizes a deep learning model (YOLOv8 or similar) to perform real-time vehicle detection and count at an intersection. Based on the calculated traffic density, a control algorithm dynamically adjusts the traffic light timings to minimize waiting time and optimize flow, significantly outperforming traditional fixed-timing systems. This addresses a critical urban problem by integrating AI into a core infrastructure service.
2. Drowsiness and Distraction Detection System for Drivers
The goal is to develop an Advanced Driver Assistance System (ADAS) to prevent accidents caused by driver fatigue. The system uses a webcam and Deep Learning (CNN) to monitor the driver's face, specifically calculating the Eye Aspect Ratio (EAR) and Head Pose Estimation. If a driver exhibits signs of drowsiness (closed eyes for an extended period) or distraction (looking away from the road), the system triggers an immediate audible and visible alert. This embedded solution would run efficiently on a low-power microcontroller like the ESP32-CAM or a Raspberry Pi, making it suitable for cost-effective in-vehicle integration.
☁️ IoT & Embedded Systems Projects
3. Smart Agriculture System with Predictive Analytics
Abstract:
This project designs and implements an IoT-based Smart Agriculture Monitoring and Control System. The system uses multiple sensors (soil moisture, temperature, humidity, and light intensity) connected to a microcontroller (e.g., ESP32) to gather environmental data. This data is transmitted via a wireless protocol (MQTT) to a cloud platform (e.g., AWS IoT, Google Cloud). An integrated Machine Learning model analyzes the data to predict optimal irrigation schedules and nutrient requirements, activating pumps and valves remotely, thereby conserving water and maximizing crop yield.
4. Wearable Health Monitoring Device with BLE and Cloud Integration
Abstract:
This project focuses on a non-invasive Wearable Health Monitoring System designed for continuous remote patient care. The device, built around a low-power microcontroller, uses sensors to track vital parameters such as Heart Rate, SpO2 (Blood Oxygen Level), and Body Temperature. Data is securely transmitted via Bluetooth Low Energy (BLE) to a mobile application, which then pushes the data to a secure cloud database. The system incorporates an alert mechanism (SMS or notification) for doctors or caregivers if any vital sign falls outside a safe threshold, facilitating real-time remote monitoring and intervention.
📡 Communication & RF Projects
5. Wireless Power Transfer System for Electric Vehicle Charging
Abstract:
The objective is to design and prototype a Magnetic Resonance-based Wireless Power Transfer (WPT) system for static or semi-dynamic charging of low-power Electric Vehicles (EVs) or mobile devices. The project involves designing the transmitter and receiver coils, the high-frequency inverter circuit to drive the transmitter, and a rectifier/regulator circuit for the receiver. The system aims to achieve a high transfer efficiency ($\eta$) over a medium air gap, demonstrating a more convenient and robust alternative to wired charging.
6. Designing an SDR-based GSM/GPS Receiver
Abstract:
This project explores the field of Software-Defined Radio (SDR) by implementing a basic receiver for GSM (Global System for Mobile Communications) or GPS (Global Positioning System) signals using an affordable RTL-SDR dongle and a software platform like GNU Radio. The project involves understanding digital signal processing concepts like sampling, filtering, and demodulation. The goal is to extract meaningful information from the received radio frequency (RF) signals, such as location coordinates (for GPS) or cell tower identifiers (for GSM), providing practical exposure to modern communication system architecture.
❓ Final Year Project FAQs (ECE 2025)
Q1: Which programming languages are essential for these projects?
The most essential languages depend on the domain:
Python is crucial for all AI/ML and Computer Vision projects (like the Traffic and Drowsiness systems), primarily using libraries like TensorFlow, PyTorch, and OpenCV.
C/C++ is fundamental for efficient Embedded Systems and Microcontroller programming (for the IoT and Wearable devices).
JavaScript/HTML/CSS are needed if your project involves a Web-based dashboard or user interface (common in IoT projects).
Q2: What is the typical hardware platform needed for the AI/ML-based projects?
For real-time AI/ML projects like the Traffic Management or Drowsiness Detection systems, you'll need a platform with sufficient processing power and GPU capabilities, such as a Raspberry Pi 4 (8GB) or, preferably, an NVIDIA Jetson Nano/Xavier NX. For simpler sensor reading and data transmission (like the IoT farm), an ESP32 or Arduino is sufficient.
Q3: How do I handle data storage and security for the IoT and Health Monitoring projects?
Data from the edge devices (sensors/wearables) should be transmitted using secure protocols like MQTT over TLS/SSL.
Storage should utilize reliable cloud services like AWS IoT, Google Cloud Platform (GCP) IoT Core, or Microsoft Azure IoT Hub. These platforms offer secure ingestion, storage (e.g., in a NoSQL database like MongoDB), and scalable data processing.
Q4: Are the SDR (Software-Defined Radio) and Wireless Power Transfer projects practical for a final year project?
Yes, they are highly practical and technically challenging.
The SDR project focuses on Digital Signal Processing (DSP) and Communication Theory, using affordable hardware like the RTL-SDR and open-source software like GNU Radio.
The Wireless Power Transfer (WPT) project is excellent for demonstrating Power Electronics and RF Circuit Design skills, typically involving building a prototype that transfers a small amount of power (e.g., 5W) to measure and optimize efficiency.
Q5: What is the key innovation in the Smart Agriculture project compared to older versions?
The key innovation is the shift from simple monitoring to Predictive Analytics. Older systems only report current soil conditions. The latest 2025 version integrates a Machine Learning model (often a regression or time-series model) that analyzes historical data to predict the optimal time and amount for irrigation before the soil reaches a critical dry level, leading to more efficient resource use and better crop health.
For all project list blog posts click: Index Page for Project Titles List
...till the next post, bye-bye & take-care.
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