Sonar Technology Assisted Vehicle Sensor
Partick Anthony C. Roca1, Emalyn A. Pabello2, John Rey B. Reyes3, Romiel C. Sabarillo4, Ranil P. Sumook5, Arvin Anthony S. Araneta6
1Patrick Anthony C. Roca*, BS Computer Science, College of Information & Communication Technology, Eastern Samar State University – Salcedo Campus, Salcedo, Eastern Samar, Philippines.
2Emalyn C. Pabello, BS Computer Science, College of Information & Communication Technology, Eastern Samar State University – Salcedo Campus, Salcedo, Eastern Samar, Philippines.
3John Rey B, Reyes, BS Computer Science, College of Information & Communication Technology, Eastern Samar State University – Salcedo Campus, Salcedo, Eastern Samar, Philippines.
4Romiel C. Sabarillo, BS Computer Science, College of Information & Communication Technology, Eastern Samar State University – Salcedo Campus, Salcedo, Eastern Samar, Philippines.
5Ranil P. Sumook, BS Computer Science, College of Information & Communication Technology, Eastern Samar State University – Salcedo Campus, Salcedo, Eastern Samar, Philippines.
6Arvin Anthony S. Araneta, Assistant Professor I, College of Information & Communication Technology, Eastern Samar State University – Salcedo Campus, Salcedo, Eastern Samar, Philippines.
Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 2505-2510 | Volume-8 Issue-4, November 2019. | Retrieval Number: D7032118419/2019©BEIESP | DOI: 10.35940/ijrte.D7032.118419
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In the Philippines, more than half of its vehicular accidents are caused by motorcycles, and most of the reasons why these accidents are happening is because of distracted driving, lowered road awareness, delayed response to emergency such as accidents, and over speeding to name a few as confirmed by World Health Organization’s reports. Premised on this idea, the researchers decided to design, develop, and test a device that would provide a solution to this. Thus, the title “Sonar Technology Assisted Vehicle Sensor” was created. The device was completed after three months of research and development in Eastern Samar State University Salcedo Campus. Results of the four-stage test: the Benchmark; Alpha; Beta; and Usability tests indicated that the Sonar Technology Assisted Vehicle Sensor is fully functional and can detect vehicles approaching and can produce corresponding alarms, and can now be implemented. As an additional feature, the device has been imbedded with a Global Positioning System (GPS) Tracker that activates whenever an accident happens to the user/rider. The GPS Tracker would extract the device’s location and the system would automatically send the data to appropriate authorities using its Global System for Mobile Communications (GSM) shield through text messaging. The researchers recommend that the device should be marketed directly to motorcycle companies; its GPS system should be submitted for further testing, while the image processing should be trained in computers with RAM size of 8 GB and should be tested paired with an infrared lamp to maximize its use in night time traveling conditions.
Keywords: Sonar-Assisted Device, Image Processing, Multi-Processor.
Scope of the Article: Image Processing and Pattern Recognition.