IOT Based Industrial Fault Monitoring Sysytem

Internet of Things (IoT) is rapidly increasing technology. IOT is the network of physical objects or things embedded with electronic software, sensors, and network connectivity which enables these objects to collect and exchange data. IOT then deals with bringing control of physical devices over the

2025-06-28 16:33:35 - Adil Khan

Project Title

IOT Based Industrial Fault Monitoring Sysytem

Project Area of Specialization Internet of ThingsProject Summary

Internet of Things (IoT) is rapidly increasing technology. IOT is the network of physical objects or things embedded with electronic software, sensors, and network connectivity which enables these objects to collect and exchange data. IOT then deals with bringing control of physical devices over the internet.

Automated factories and processes are too expensive to be rebuilt for every modification and design change, so they have to be highly configurable and flexible. In our project, we will be developing a system which will automatically monitor the industrial applications and generate Alerts/Alarms or make intelligent decisions using the concept of IoT. A number of sensors are deployed in our project to monitor industrial parameters like temperature, fire, gas, etc. These parameters are carefully selected on the basis of the potential hazards they can cause to the normal working of the industry machine.

The sensors used in our project are Temperature and humidity sensor DHT11, Gas sensor MQ2, Flame sensor LM393, Pressure sensor (BMP180) and PIR sensor. These sensors will collect their respective data and then send the same data Raspberry Pi 4 model B which is minicomputer and we can do everything on it , it will sends data to the internet with its built in wifi capabilities. The data in the internet will be received by Thingspeak which is used for data collection in the cloud with advance data analysis using Matlab.

The data from the sensors continuously send to thingspeak through Raspberry pi. If anything happens like gas leakage or fire breakdown then the data can be shown on the graphs of thingspeak and a buzzer with RED light alert will be ON within the field and also will be seen on LCD screen in the industry. For early precautions there will be a Fan which will be on as fire or smoke occurs.

Project Objectives Project Implementation Method

In this proposed system we are going to use the Cortex-A72 (ARM v8) architecture based raspberry pi 4 it has 64-bit quad-core processor, dual-display support at resolutions up to 4K via a pair of micro-HDMI ports, hardware video decode at up to 4Kp60, up to 4GB of RAM, dual-band 2.4/5.0 GHz wireless LAN, Bluetooth 5.0, Gigabit Ethernet, USB 3.0, and PoE capability (via a separate PoE HAT add-on).it speed ups the execution process it is having  Cortex-A72 architecture. It is used to minimize the system hardware .and it is having inbuilt Ethernet port.

The software tools for programming will be used are: RASPBIAN (OS) which is s a free operating system for the raspberry pi hardware. And Python IDLE (Integrated Development Environment) editor which is a graphical user interface for Python development. This GUI is free and installed automatically during the Python installation. It enables you to edit, run, and debug Python programs in a simple GUI environment.

Benefits of the Project Technical Details of Final Deliverable

After the starting of project and initializing the sensors, the data from the sensors will be send to raspberry pi GPIO pins for processing. The GPIO Pins are set as output or input that is set by coding through RASPBIAN which is operating system for raspberry pi hardware and Python IDLE in which we code for complete system. After saving the data and connected to wifi the data will be stored at Server in the form of .CVS file and send to Cloud. The data will receive by client via ThingSpeak.com using HTPP protocol can be analyzed on any computer or phone.

Flow Diagram :

Initilization of sensors

Data from Input Sensors to Raspberry Pi Processor

Data Stored in CVS file at Server

Data from Server Send to Clint side using Thingspeak by HTPP protocol

   Stop

The finalized Sensors which are utilized in this project are:

Sensors

Specification

Gas sensor

MQ2 or MQ9

Flame sensor

LM393

Temperature & humidity sensor

DTH11 or DTH22

PIR sensor

HC-SR501

Pressure Sensor

BPM180

Initilization of sensors

Data from Input Sensors to Raspberry Pi Processor

Data Stored in CVS file at Server

Data from Server Send to Clint side using Thingspeak by HTPP protocol

   Stop

Sensors

Gas sensor

Flame sensor

Temperature & humidity sensor

PIR sensor

Pressure Sensor

Final Deliverable of the Project HW/SW integrated systemCore Industry SecurityOther Industries Manufacturing Core Technology Internet of Things (IoT)Other TechnologiesSustainable Development Goals Industry, Innovation and InfrastructureRequired Resources

Data from Input Sensors to Raspberry Pi Processor

More Posts