![]() The ability of the technique to discern different types of speed bumps while travelling in a variety of vehicle types has been demonstrated. Also, the use of pass filters to extract the signal of concern from the noisy data has been exhibited. The importance of using a mathematical model to understand the acceleration response of a vehicle has been established. The acceleration signals have been digitally processed to capture road bumps. A time averaging technique has been employed to compress the collected data. Filters have been used to reduce noise in the signals. The experiment is repeated for different classes of vehicles. The acceleration response of the phone while passing over the corresponding road bumps, which was used in the model earlier, is recorded using an Android based application. The accelerometer of a smartphone is validated by comparing it with high precision accelerometers. The mathematical model of the vehicle is excited with parameters analogous to some common speed bumps and its acceleration response is calculated. MethodsĪ range of road vehicles is mathematically modelled as mass, spring, and damper systems. However, the capability of the smartphone in discerning different types of speed bumps while travelling in heterogeneous vehicle types needs to be examined. This can empower the user community in monitoring of roads. The smart mobile phones have accelerometers and position sensors that can be useful for autonomous monitoring roads. This paper demonstrates the capability of smartphones placed inside the vehicles in characterisation of road bumps. Fortuitously, the roadways and mobile phone networks have grown simultaneously in emerging economies. It is not too infrequent, especially in the emerging economies, to have unmarked bumps that can be perilous for the passengers. Speed bumps are used as the main means of controlling vehicle speeds all over the world.
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