Industrial Protection System using Arduino and IoT

2021 ◽  
Vol 7 (2) ◽  
Author(s):  
A. Parvathi ◽  
S. Imran Basha ◽  
M. Jayanth Kumar ◽  
B. Chandra Sekhara Bhagavan ◽  
P. Dinesh Reddy
Keyword(s):  
Fire Detection ◽  
Record Values ◽  
Temperature Sensors ◽  
Protection System ◽  
Sensor Data ◽  
Industrial Accidents ◽  
Low Light ◽  
Ir Sensor ◽  
Gas Leaks ◽  
Poor Lighting

The Industrial protection system designed using Arduino and IOT mainly focuses on the protection of industries from various losses occurring due to accidents caused due to improper conditions and maintenance. Gas leaks can cause fires that cause huge industrial losses; Instant fire detection is also required in the event of a furnace explosion or other conditions. Additionally, poor lighting in industries can create unsuitable working conditions, increasing the likelihood of accidents. The system uses Arduino to achieve this functionality. The system uses temperature sensors in combination with gas light sensors to detect fires, gas leaks, and low light to prevent industrial accidents and avoid leaks. These setups also work as an anti-theft security system where it utilizes the IR sensor to detect the objects coming in its path. So this IR sensor works with the help of direct incidence of radiation on the photodiode. This IR LED which is placed on one side of the board and the photodiode is placed on the other helps to detect any obstacle or object which comes closer to contact with it. This object detection is indicated with the help of an alarm to notify us. The system consists of light, gas, and temperature sensors interconnected with Arduino and LCD screens. Sensor data is constantly scanned to record values and check for fire, gas leaks, or poor lighting, and then this data is transmitted online. The Wi-fi module is used to achieve internet functionality. The Blynk server then displays this information online, to achieve the desired result.

scholarly journals A Smart WiFi Multi-Sensor Node for Fire Detection Mechanism Based on Social Network

2018 ◽  
Vol 14 (10) ◽  
pp. 4
Author(s):  
Anekwong Yoddumnern ◽  
Roungsan Chaisricharoen ◽  
Thongchai Yooyativong
Keyword(s):  
Sensor Node ◽  
Finite Impulse Response ◽  
Fire Detection ◽  
Sensor Data ◽  
Sensor Calibration ◽  
Sensing Element ◽  
Detection Mechanism ◽  
Small Device ◽  
Home Area ◽  
Calibration Time

<p class="0abstract">A small device with WiFi multi-sensing element is very important under a social digital century<strong>.</strong> This study aims to implement the hardware and the power of the algorithm with WiFi technologies. Especially, the multi-sensors have to reinforce around a home area and support to any requirement in the term of digital society. This study focus to care the home security— on going to the fire detection with applying several technologies based on a Cloud. Firstly, the multi-sensor calibration has used calibration time and self-calibration as the Finite Impulse Response (FIR). Next, the Full-Scale Kalman Filter (FSKF) helps to fill data and estimate the accuracy data. After that, the fire detection mechanism has used Fuzzy logic to detect and send alert messages over an IFTTT process. There are changed following event-- the data range of fire proportion inside the home. Furthermore, The OFF-Mode has reduced the power consumption suddenly the WiFi module is sent the sensor data to the Cloud. Finally, the WiFi multi-sensor node will use more than one sensor as the same detector will be a high stability and high accuracy.</p>

scholarly journals Sistem Pemantauan Dapur Menggunakan Teknologi Hybrid WiFi - Visible Light Communication

2021 ◽  
Vol 13 (1) ◽  
pp. 39-43
Author(s):  
Denny Darlis ◽  
Aris Hartaman ◽  
Afifah Shafira
Keyword(s):  
Visible Light ◽  
Gas Sensors ◽  
Data Transmission ◽  
Fire Detection ◽  
Visible Light Communication ◽  
Sensor Data ◽  
Test Results ◽  
Final Project ◽  
Parameter Values ◽  
Monitor Data

Visible Light Communication (VLC) is a technology that allows the sending of data information through visible light that will be received as a piece of information. In its implementation, a sensor can send information data using VLC in this technological era. One model of data transmission that is widely used in life is to use radio frequency or better known as wireless.In this final project, a transmitter and receiver of data is realized through the transmission of light, this device consists of a lamp as an electrical converter to light, a photodioda as a converter of light to electric, and receiving data. Through the realization of this tool we can know that the transmission of data through light can occur can be used to transmit data. Data transmitted in this final project is the result of three sensor data namely temperature sensors, gas sensors, and fire detection sensors on the transmitter and on the receiver used firebase to monitor data. From the test results produce parameter values such as distance with a maximum distance of the data is accepted either 45cm, 50cm of data is damaged and 55cm of data is not accepted, the variations in angles and distances show that at a distance of 10cm it can receive data well from an angle of 0ᵒ to an angle of 35ᵒ, a distance of 35cm and 40 cm at an angle of 10ᵒ the received data is damaged and at a distance of 45cm and 50cm at a 5ᵒ angle cannot receive data and as well as the sending speed parameters obtained at a baudrate of 2400 bps, 4800 bps and 9600 bps the data sent can be received well.

scholarly journals DESIGN AND ANALYSIS OF AN INTELLIGENT FIRE DETECTION SYSTEM FOR AIRCRAFT

2020 ◽  
Vol 5 (2) ◽  
pp. 260-273
Author(s):  
Amit Yadav ◽  
Abhijeet Agawal ◽  
Pramod Kumar ◽  
Tejaswi Sachwani
Keyword(s):  
Neural Network ◽  
Detection System ◽  
Fire Detection ◽  
Sensor Data ◽  
Correct Prediction ◽  
The Neural Network ◽  
Fire Condition ◽  
Fire Alarm System ◽  
Actual Fire ◽  
Fire Detection System

Fire detection system and fire warning are design features of an aircraft. Fire detection system protects the aircraft and passengers both in case of actual fire during flight. But spurious fire warning during flight creates a panic situation in flight crews and passengers. The conventional fire alarm system of an aircraft is triggered by false signal. ANN based fire detection system provides real observation of deployed zones. An intelligent fire detection system is developed based on artificial neural network using three detection information such as heat (temperature), smoke density and CO gas. This Information helps in determining the probability of three representative of Fire condition which is Fire, smoke and no fire. The simulated MATLAB results Show that the errors in identification are very less. The neural network based fire detection system integrates different types of sensor data and improves the ability of system to correct prediction of fires. It gives early alarm when any kind of fire broke out and helps to decrease in spurious warning.

IEEE 1451-Based Sensor Interfacing and Data Fusion for Fire Smoke Detection

2014 ◽  
Vol 613 ◽  
pp. 219-227
Author(s):  
Chao Ching Ho ◽  
Dan Wen Kuo
Keyword(s):  
Video Processing ◽  
Detection System ◽  
Fire Detection ◽  
Sensor System ◽  
Sensor Data ◽  
Smoke Detection ◽  
Fire Smoke ◽  
Ieee 1451 ◽  
Smart Transducer ◽  
Transducer Interface

The performance of a fire sensor has a significant effect on fire detection. Today’s fire alarm systems, such as smoke and heat sensors, however are generally limited to a close proximity to the fire; and cannot provide additional information about fire circumstances. Thus, it is essential to design a suite of low-cost networked sensors that provide the capability of performing distributed measurement and control in real time. In this work, a wireless sensor system was developed for fire detection. The purpose of this paper is to analyze the integration of traditional fire sensors into intelligent fire management systems by using the smart transducer concept. An automated video processing sensor for fire smoke monitoring applications is integrated into an surveillance network as a case study and supported sensor fusion assessment to improve the resistance to nuisance alarms. The proposed sensor system for fire detection was developed to reconcile issues related to proliferation and interoperability, and the architecture can support a smart transducer interface (IEEE 1451). The proposed embedded system for STIM (smart transducer interface module) and NCAP (network capable application processor) will be implemented with DSP. To realize the self-identification of transducers and plug-and-play connections, a transducer electronic data sheet (TEDS) is also stored inside the DSP. The acquired sensor data are pre-processed and applied to discriminate nuisance sources. The IEEE 1451 standard has been integrated into an automatic video-based fire smoke detection system. The proposed architecture has been tested on an experimental setup with the purpose of monitoring fire incidents successfully.

scholarly journals Hybrid Architectural Network Implementation to Realize a Fire Evacuation Path with 2.4 GHz Zigbee and LoRa

2021 ◽  
Vol 13 (23) ◽  
pp. 13238
Author(s):  
Rajesh Singh ◽  
Gajanand S. Birajdar ◽  
Mamoon Rashid ◽  
Anita Gehlot ◽  
Shaik Vaseem Akram ◽  
...  
Keyword(s):  
Real Time ◽  
Fire Detection ◽  
Sensor Data ◽  
Delivery Ratio ◽  
Hybrid Architecture ◽  
Medium Access ◽  
Fire Event ◽  
Sensory Data ◽  
Link Budget ◽  
Safety Operation

The Internet of Things (IoT) is playing a significant role in realizing real monitoring. In fire safety and evacuation, early fire event detection using IoT-enabled sensors may help to control and minimize further consequences of the fire accident. In this study, we propose a hybrid architecture based on 2.4 GHz Zigbee and long-range (LoRa) for real-time fire detection, monitoring, and assisting in the safe evacuation of the building. The architecture comprises five different components, namely: end device, evacuation path display controller, safety operation controller, vision node, and gateway. The end device and vision node provide real-time sensory data and visuals that provide details of fire occurrence. The evacuation path display controller and the safety operation controller based on the 2.4 GHz Zigbee receive data from the end device and make the decision accordingly. In addition, a Zigbee simulation is performed on the OPNET simulator to analyze the network parameters such as throughput, retransmission attempts, medium access (MAC) queue size and queue delay, and packet delivery ratio (PDR). The evaluation metrics of link budget and ToA of LoRa are also calculated by varying the code rate and spreading factor. To realize the proposed architecture, customization of hardware is carried out with the development of hardware prototypes. Dijkstra’s shortest path algorithm is implemented in the evacuation path display controller to provide the shortest evacuation path during a fire incident. The hardware of the system is implemented in real-time, and the system provides real-time sensor data along with the evacuation path.

An Analysis of the Efficacy of Wayside Hot-Box Detector Data

2018 ◽  
Author(s):  
Constantine Tarawneh ◽  
James A. Aranda ◽  
Veronica V. Hernandez ◽  
Claudia J. Ramirez
Keyword(s):  
Field Test ◽  
Dynamic Test ◽  
Operating Conditions ◽  
Temperature Measurements ◽  
Sensor Data ◽  
Similar Distribution ◽  
Infrared Sensor ◽  
Ir Sensor ◽  
The University ◽  
Class F

Wayside hot-box detectors (HBDs) are devices that are currently used to monitor bearing, axle, and brake temperatures as a way of assessing railcar component health and to indicate any possible overheating or abnormal operating conditions. Conventional hot-box detectors are set to alarm whenever a bearing is operating at a temperature that is 94.4°C (170°F) above ambient, or when there is a 52.8°C (95°F) temperature difference between two bearings that share an axle. These detectors are placed adjacent to the railway and utilize an infrared sensor in order to obtain temperature measurements. Bearings that trigger HBDs or display temperature trending behavior are removed from service for disassembly and inspection. Upon teardown, bearings that do not exhibit any discernible defects are labeled as “non-verified”. The latter may be due to the many factors that can affect the measurement of HBDs such as location of the infrared sensor and the class of the bearing among other environmental factors. A field test was performed along a route that is more than 483 km (300 mi) of track containing 21 wayside hot-box detectors. Two freight cars, one fully-loaded and one empty, and one instrumentation car pulled by a locomotive were used in this field test. A total of 16 bearings (14 Class F and 2 Class K) were instrumented with K-type bayonet thermocouples to provide continuous temperature measurement. The data collected from this field test were used to perform a systematic study in which the HBD IR sensor data were compared directly to the onboard thermocouple data. The analyses determined that, in general, HBDs tend to overestimate Class K bearing temperatures more frequently than Class F bearing temperatures. Additionally, the temperatures of some bearings were underestimated by as much as 47°C (85°F). Furthermore, the HBD data exhibited some false trending events that were not seen in temperature histories recorded by the bayonet thermocouples. The findings from the field test suggest that HBDs may inaccurately report bearing temperatures, which may contribute to the increased percentage of non-verified bearing removals. To further investigate the accuracy of the wayside detection systems, a dynamic test rig was designed and fabricated by the University Transportation Center for Railway Safety (UTCRS) research team at the University of Texas Rio Grande Valley (UTRGV). A mobile infrared sensor was developed and installed on the dynamic tester in order to mimic the measurement behavior of a HBD. The infrared temperature measurements were compared to contact thermocouple and bayonet temperature measurements taken on the bearing cup surface. The laboratory-acquired data were compared to actual field test data, and the analysis reveals that the trends are in close agreement. The large majority of temperature measurements taken using the IR sensor have been underestimated with a similar distribution to that of the data collected by the HBDs in field service.

Application of Common-Use Temperature Sensors to Early Fire Detection

2019 ◽  
pp. 755-766
Author(s):  
Daisaku Nii ◽  
Mai Namba ◽  
Kazunori Harada ◽  
Ken Matsuyama ◽  
Takeyoshi Tanaka
Keyword(s):  
Fire Detection ◽  
Temperature Sensors ◽  
Early Fire Detection
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