Location: Jalan Sultan Yahya Petra, Kuala Lumpur Malaysia
Company: Universiti Teknologi Malaysia
Number of times previously entering contest: 2
Inspired by: In order to establish a resilient network transportation that could handle flash flood disaster, a multi-step framework should be developed. The systematic effort of the mitigation consists of the development of statistical prediction that can be trained dynamically based on the trend of the datasets obtained from the IoT nodes deployed on the real environment. The model performances will be validated and bench marked with the outperform models that have been used in other fields. There are many manipulated variable that can be tune around in order to increase the performance of the model such as manipulation of the weight values of the algorithm, the training parameters such as number of epochs, learning rate and the architecture structural of the model.
|06/13||Flood Mitigation Strategy for Network Transportation in Urban Areas via Implementation of IoT||Electronics/Sensors/IoT||225||1|