Anuar, Muhammad Zahirulhaq Zainol and Zambri, Nor Aira and Salim, Norhafiz and Yi, Sim Sy and Hassan, Omar Abu (2023) Automated bicycle crash detection system. In: 3rd International Conference on Electrical and Electronics Engineering 2021: Versatility of Electrical and Electronics Engineering Solutions for Sustainable Future, ICON3E 2021, 6 September 2021 through 7 September 2021, Virtual, Online.
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Abstract
Road accidents rate are now very high, especially for two-wheeled vehicle. It is necessary to have a sort of road accident detection and information system to rescue the injured victims. This research aims to create a prototype of an ABCDs that is implemented at a bicycle. The main target is to minimize the accident’s response time whenever accident occurs. The accident detection uses the ESP8266 Node MCU, smartphones, GSM and GPS technology, AXL 335 accelerometer and Blynk for mobile applications. The input is an accelerometer that detects the shock and Node MCU will send the location via Email or mobile phone. The GPS receiver module detects geographical coordinates of the area and signal message will be sent through GSM. To validate the prototype, three separated tests were conducted andthe test was performed for various type of open area, closed area, with different fixed value test as well. Testing data shows that the prototype successfully detected crash or accident and notification was successfully delivered through Blynk. Inevitably, this project help in providing assistance for the accident victims in emergency situations within short period of time. Indeed, with a proper setup and adjustment, this prototype benefits riders in helping everyone’s helps lives because life was a blessing for everybody,
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | Measuring instruments, Telecommunications engineering |
| Divisions: | Faculty Of Electrical Technology And Engineering |
| Depositing User: | Anis Suraya Nordin |
| Date Deposited: | 17 Oct 2024 15:41 |
| Last Modified: | 17 Oct 2024 15:41 |
| URI: | http://eprints.utem.edu.my/id/eprint/28066 |
| Statistic Details: | View Download Statistic |
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