Real-Time-Leak-Detection-in-Infrastructure uses sensors, machine learning, and data analytics to continuously monitor pipelines and water systems. It detects anomalies such as sudden pressure drops or unusual flow patterns, enabling early leak identification

**Water-Pollution-Detection-via-Satellite-Imagery** uses artificial intelligence to analyze satellite images and identify polluted water bodies. The system applies image processing and machine learning techniques to detect contamination patterns and classify water quality

Image watermark with Convolutional Neural Networks

Abstract Semantic Textual Similarity (STS) measures the meaning similarity of sentences. Applications of this task include machine translation, summarization, text generation, question answering, short answer grading, semantic search, dialogue and conversational systems. We developed Support Vector Regression model with various features including the similarity scores calculated using alignment-based methods and semantic composition based methods. We have also trained sentence semantic representations with BiLSTM and Convolutional Neural Networks (CNN). The correlations between our system output the human ratings were above 0.8 in the test dataset. Introduction The goal of this task is to measure semantic textual similarity between a given pair of sentences (what they mean rather than whether they look similar syntactically). While making such an assessment is trivial for humans, constructing algorithms and computational models that mimic human level performance represents a difficult and deep natural language understanding (NLU) problem. Example 1: English: Birdie is washing itself in the water basin. English Paraphrase: The bird is bathing in the sink. Similarity Score: 5 ( The two sentences are completely equivalent, as they mean the same thing.) Example 2: English: The young lady enjoys listening to the guitar. English Paraphrase: The woman is playing the violin. Similarity Score: 1 ( The two sentences are not equivalent, but are on the same topic. ) Semantic Textual Similarity (STS) measures the degree of equivalence in the underlying semantics of paired snippets of text. STS differs from both textual entailment and paraphrase detection in that it captures gradations of meaning overlap rather than making binary classifications of particular relationships. While semantic relatedness expresses a graded semantic relationship as well, it is non-specific about the nature of the relationship with contradictory material still being a candidate for a high score (e.g., “night” and “day” are highly related but not particularly similar). The task involves producing real-valued similarity scores for sentence pairs. Performance is measured by the Pearson correlation of machine scores with human judgments.

This repository contains the coding aspect of the project Leakage Detection in Smart Water Distribution Systems, where the collected data is used for training an ANN model to detect leakage.

Whole house water leak detection and water shutoff system. Requires a supervisory computer for full functionality. Communications is via MQTT.

A smart IoT-based water leakage detection system that monitors water flow in real-time using ESP32 microcontroller. The system compares flow rates from two sensors to detect leaks and automatically shuts off the water supply when a discrepancy is detected.

This is an application for automation of gardening process which includes Temperature control, Watering system, Soil testing for fertilizers, Fire detection, Rain Detection

Smart India Hackathon 2025 project featuring water management system frontend. Includes water usage monitoring, leak detection visualization, consumption analytics, automated alerts, and resource optimization tools to promote sustainable water management practices.

leak detection system in under water

An intelligent water pipeline monitoring and leakage detection system that leverages Machine Learning, Signal Processing, Feature Extraction and Frequency Analysis of sound to identify leakage in pipelines and smart homes.

In collaboration with I.B.M. & Clemson University, this repository contains code for the water stress detection system developed by the Watson-in-the-Watt creative inquiry team. We are developing a networked visual recognition system which leverages IBM's cognitive intelligence, Watson, to detect water stress in ornamental shrubs.

An approach for anomaly detection in Industrial Control Systems (ICS), using Water Treatment Dataset (SWaT). The implementation incorporates cutting-edge machine learning techniques, including Isolation Forest and Autoencoder models, augmented by Dynamic Time Warping (DTW) algorithm.

Big Data Framework for Anomaly Detection in Secure Water Treatment Systems.

Developed Homie, an IoT-based home automation system that monitors and controls utilities including water pump automation, gas leak detection, temperature monitoring, and security alerts. Features custom PCB design in Proteus with mobile app integration for remote monitoring and control of smart home devices.

No description available

基于机器学习的水位异常检测系统

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Water Level Monitoring System in Water Tanks can be used in Houses to avoid overflow and wastage of water. In this project, one of the important parts is the High Sensitivity Water Sensor. It is easy to use, light in weight, compact in size, high identification, and detection of water, droplets.

Active Contamination Detection in Water Distribution Systems

No description available

The water level controller and water pump automation system has been built using an arduino uno microcontroller board. A water level sensor and ultrasonic sensor are installed on the overhead tank to enable detection of water level.

Build An IOT Sensor based water Safety Detection System

Big Data Framework for Anomaly Detection in Secure Water Treatment Systems. visualize summaries of the data stream(s) and develop an ML model to detect anomalies in the data set.

Automated water leakage detection systems can help the different sectors of the world a lot by saving water wastage. This project is an attempt to illustrate implementation of water leakage detection and monitoring system using the applications of Internet of Things (IoT).

Real-time pollution detection system with water and air quality modules.

This constitutes a model and web-based python system for detection of anomalies in water consumption

Simulation code for the paper: "Covert System Identification Attacks and Detection in Water Treatment Control Systems". Implements stealthy MitM attacks and evaluates PASAD and CUSUM detection under varying noise and model error conditions.

Fire Extinguish Robot using ESP32 | Bluetooth-controlled firefighting robot with obstacle avoidance, flame detection, and water pump system. Controlled via PC app.

Road Hazard Detection Project: AI-driven system for real-time detection of road hazards like snow, ice, and water. Developed with Valeo sponsorship. University of Ottawa AI and Data Science project.