Print Email Facebook Twitter Development of an Integrated Bicycle Accident Detection System Title Development of an Integrated Bicycle Accident Detection System: Introducing ALARM: Accident Localisation And Recognition Method Author Kuiper, Joris (TU Delft Mechanical, Maritime and Materials Engineering; TU Delft Cognitive Robotics; TU Delft Biomechanical Engineering; Koninklijke Gazelle) Contributor Schwab, A.L. (mentor) Moore, J.K. (mentor) Happee, R. (graduation committee) Degree granting institution Delft University of Technology Programme Mechanical Engineering Date 2021-06-28 Abstract Bicycles connected to the internet present an opportunity for integrated accident detection and geolocation. Such a system can reduce the time it takes for help to arrive by automatically alerting predefined contacts with the location of the accident. I developed a systematic method for the practical implementation of bicycle accident detection in connected bicycles and present the performance of a prototype system. The method uses accelerometer and gyroscopic measurements as well as localization and velocity estimations. Supplementing existing research, a bicycle accident detection system is validated on normal cycling, edge cases, and three types of single bicycle accidents with constraints set by a bicycle manufacturer. Edge cases are movements of a bicycle that occur during regular usage, but can not be described by normal cycling. This method uses a data¬driven approach. For the prototype system, the input signals are collected during 71 different simulated accidents and 54 hours of normal cycling and edge cases. A three¬layer detection algorithm determines if an accident has occurred and sends the last known location to a set of predefined contacts. Multiple combinations of thresholds and classification algorithms are compared. This resulted in a prototype system with a K¬Nearest Neighbours classifier which detects 75% of accidents. Normal cycling and edge cases are correctly detected 99.997% of the time. From all warnings send, 85.7% are true accidents. The prototype system proves that the proposed method can be used to integrate reliable accident detection in connected bicycles. Bicycles with such a system automatically inform emergency contacts with a message containing the location of the accident, in a time where every second counts. Subject BicycleAccidentCrashDetectionFallEmergencyLocalisation To reference this document use: http://resolver.tudelft.nl/uuid:171087f3-4ff5-458c-9065-334958ca7b72 Embargo date 2023-06-28 Part of collection Student theses Document type master thesis Rights © 2021 Joris Kuiper Files PDF Development_of_an_Integra ... Method.pdf 19.23 MB Close viewer /islandora/object/uuid%3A171087f3-4ff5-458c-9065-334958ca7b72/datastream/OBJ/view