Design and implementation of a smart bike accident detection system
| bracu.type.group | Research Publications | |
| datacite.rights | Metadata Only | |
| dc.contributor.author | Islam M.M. | |
| dc.contributor.author | Ridwan, A. E. M | |
| dc.contributor.author | Mary, Mekhala Mariam | |
| dc.contributor.author | Siam, Md Fahim | |
| dc.contributor.author | Mumu, Sadia Anika | |
| dc.contributor.author | Rana, Shohag | |
| dc.contributor.department | Department of Computer Science and Engineering | |
| dc.date.accessioned | 2026-09-02T04:18:28Z | |
| dc.date.available | 2026-09-02T04:18:28Z | |
| dc.date.issued | 2020-06-05 | |
| dc.description.abstract | Nowadays overpopulated countries like Bangladesh have become a warzone where thousands of people lose their lives and even more become handicapped due to road accidents. With the recent popularity of ride sharing apps like Pathao, Uber Moto, Shohoz etc. the number of bikes in Dhaka city has increased drastically. As bike accidents are becoming quite an alarming issue, we felt the need of an improved bike safety system. In this paper, we have proposed a system that detects bike accidents using MPU6050 (gyro sensor and accelerometer), SIM808 (GPS+GPRS+GSM), Raspberry Pi 3 Model B and Arduino Uno. We have placed the proposed system on the surface of the bike. If an accident occurs, the sensors will trigger and send a message containing the number and location of the biker to the nearest hospitals, police stations and registered family members. | |
| dc.description.version | Published | |
| dc.format.extent | 386-389 | |
| dc.identifier.citation | M. M. Islam, A. E. M. Ridwan, M. M. Mary, M. F. Siam, S. A. Mumu and S. Rana, "Design and Implementation of a Smart Bike Accident Detection System," 2020 IEEE Region 10 Symposium (TENSYMP), Dhaka, Bangladesh, 2020, pp. 386-389, doi: 10.1109/TENSYMP50017.2020.9230656. | |
| dc.identifier.doi | 10.1109/TENSYMP50017.2020.9230656 | |
| dc.identifier.issn | 9781728173665 | |
| dc.identifier.other | 2-s2.0-85096422634 | |
| dc.identifier.uri | https://hdl.handle.net/10361/29678 | |
| dc.language.iso | en_US | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
| dc.relation.hasversion | 10.1109/TENSYMP50017.2020.9230656 | |
| dc.relation.ispartof | 2020 IEEE Region 10 Symposium Tensymp 2020 | |
| dc.relation.ispartofseries | 2020 IEEE Region 10 Symposium Tensymp 2020 | |
| dc.relation.uri | https://ieeexplore.ieee.org/document/9230656 | |
| dc.rights | false | |
| dc.subject | Arduino uno | |
| dc.subject | GPS | |
| dc.subject | MPU6050 | |
| dc.subject | Raspberry Pi 3 Model B | |
| dc.subject | SIM808 | |
| dc.subject.lcsh | Machine learning. | |
| dc.title | Design and implementation of a smart bike accident detection system | |
| dc.type | Conference Proceeding | |
| person.affiliation.name | United International University | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.affiliation.name | BRAC University | |
| person.identifier.scopus-author-id | 57213419679 | |
| person.identifier.scopus-author-id | 57219986123 | |
| person.identifier.scopus-author-id | 57219986248 | |
| person.identifier.scopus-author-id | 57219986136 | |
| person.identifier.scopus-author-id | 57219986421 | |
| person.identifier.scopus-author-id | 57219985977 |