Street light malfunction detection system

Abdul Rahim, Ayub (2018) Street light malfunction detection system. Faculty of Computer System & Software Engineering, Universiti Malaysia Pahang.

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Street light provides a great support and benefit to the peoples that use the road at night. It also can enhance safety for drivers or pedestrians to prevent an accident because they can see upcoming obstacle towards them with the support of light and increased the vision of them on the road. But if the street light is broken, it dangerous for the drivers and pedestrians because the probability of accident can occur is high. So, this Street Light Malfunction Detection System is developing to automatically detect the fault of street light and ease the maintenance department to do the maintenance for broken street light. The problem that need to overcome by this system are to decrease the manual registration report or report through phone call so, Street Light Malfunction Detection System is hardware applications which detect the broken street light and automatically send message to the maintenance department using Wi-Fi module. Thus, this system will help to locate which one of the street lights is broken along the road. Then, the maintainer can go direct to the broken street light to be repaired. There are a few objectives of this project which are to identify the street light malfunction factors, to develop street light malfunction detection system using Internet of Thing (IoT) and to evaluate the prototype of the street light malfunction detection system. The technique for this project is by using Internet of Things (IoT) technology which includes Arduino Uno, Light Dependent Resistor (LDR) Sensor, current sensors, LED and Wi-Fi module. The LDR sensor used to measure the intensity of light and the current sensor used to detect the current flow. So, if there is no light or the current flow, then the system will send report to the computer through Wi-Fi.

Item Type: Undergraduates Project Papers
Additional Information: Project Paper (Bachelors of Computer Science (Computer Systems & Networking)) -- Universiti Malaysia Pahang – 2018, SV: MADAM NOORHUZAIMI @ KARIMAH BINTI MOHD NOOR, e-Thesis
Uncontrolled Keywords: Street light; malfunction detection; maintenance
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Mrs. Sufarini Mohd Sudin
Date Deposited: 19 Dec 2019 04:45
Last Modified: 19 Dec 2019 04:45
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