This project is the capstone project for my bachelor’s degree @UM-SJTU Joint Institute, initiated by Prof. Mian Li. You can find the organization page on Github.

Design Overview

• IIFire, or Intelligent IoT Firefighting System, is an integrated system deployed on government servers of Shanghai fire brigade, which detects potential fire hazard and report real-life fire alarms in buildings to save people’s life and money. Currently, IIFire is connected with over 7 million IoT devices.

• IIFire provides a solution for better pre-warning of fire hazard to prevent a fire disaster, which achieves higher accuracy, less false positives, and lower response time than previous fire alarm system.

  1. With Internet-of-Thing technologies and Fuzzy Analytic Hierarchy Process algorithm deployed in edge computing devices, millions of data generated by IoT devices (especially CV cameras) are processed and send to IIFire data center immediately. The paper of our team regarding FAHP can be found here and downloaded here.

  2. IIFire has a follow-up work flow management system. Once a fire alarm or hazard are triggered, with IIFire software packages including app & website, administrator can keep an eye on the fire status anytime anywhere on any devices, and maintainers can come on spot right away when notification is forwarded to their IIFire apps.

1. Problem Statement

Nowadays, the cost and damage brought by fire disasters are heavy. According to U.S Fire Administration and National Fire Protection Association, the death number, as well as the death rate, has increased by about 3.3% over the past decades. In 2014, 1.9% of the U.S. GDP is consumed in fire protection and losses. As a result, delivering an integrated firefighting system to prevent potential fire hazards with higher reliability, greater performance, and lower cost is needed.

2. System Design

The system architecture is shown in figure below.

• The main concept of our system is based on IoT, which stands for Internet-of-Things. Raw data of firefighting devices obtained from different buildings can be connected and cooperate together. Building our own data center with database MangoDB and FAHP algorithms, cross-validations can be performed to millions of data acquired. Also, CV algorithm Yolo and ShufflenetV2 are applied on real-time fire & smoke detection through camera flow, assisting other IoT devices to decrease the false-positive rate brought by human factors.

• With processed data, user interfaces are the next critical step for staffs to take action when fire hazards are detected. With React Native and React.js, we design routine data display and safety score calculation for supervision purpose as well as emergency management workflow for both firefighting managers and maintenance workers to be noticed once anomalies occurs. The app and website are real-time synchronized through our server written in Python.

UI/UX Design Demo

Mobile App

1. Data Display

2. Notification Update (for Maintainers)

3. Building Switch (for Administrator)

4. Profile Display

Website

1. Account Login

2. Data Display

3. Workflow Management