Edge AI powered iot system for real tie water quality monitoring and intelligent aquatic environment assessments

Project Code :TEMBMA3916

Objective

To develop an Edge AI–based IoT system for continuous monitoring of water quality using multiple sensors. To process and analyze sensor data locally using machine learning for detecting changes in aquatic conditions. To enable remote monitoring and support smart water management applications such as aquaculture and environmental assessment.

Abstract

This project presents an Edge AI–powered IoT system for real-time water quality monitoring and intelligent aquatic environment assessment. The proposed system integrates an Arduino-based control unit with multiple sensors, including a pH sensor for acidity/alkalinity detection, a TDS sensor for measuring dissolved solids, a turbidity sensor for evaluating water clarity, and a DHT11 sensor for temperature monitoring. An LCD module is used to display real-time sensor readings locally, while IoT connectivity enables continuous data transmission to a cloud platform for remote monitoring and storage. Edge AI techniques are incorporated to process sensor data locally and apply machine learning models for predictive analysis, enabling early detection of water quality degradation and potential contamination. The system reduces latency, enhances decision-making, and minimizes dependence on cloud-only processing. This intelligent framework supports applications in aquaculture, environmental monitoring, and smart water management systems by providing accurate, real-time insights into aquatic conditions.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Learning Outcomes

Learning outcomes
• Arduino pin diagram and architecture
• How to install Arduino IDE / setup software
• Setting up and installation procedure for Arduino
• Introduction to Arduino development environment
• Basic programming in Arduino (C / C++)
• Basics of Embedded C / Arduino programming
• Basics of IoT platforms
• Working of power supply

• About Project Development Life Cycle:
 • Planning and Requirement Gathering (software, tools, hardware components, etc.)
 • Schematic preparation
 • Code development and debugging
 • Hardware development and debugging
 • Development of the project and output testing

• Practical exposure to:
 • Hardware and software tools
 • Solution providing for real-time problems
 • Working with team/individual
 • Work on creative ideas

• Skills developed:
 • Project development skills
 • Problem analyzing skills
 • Problem solving skills
 • Creativity and imaginative skills
 • Programming skills
 • Deployment
 • Testing skills
 • Debugging skills
 • Project presentation skills
 • Thesis writing skills

Demo Video

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