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One Model Fits All: Cross-Region Taxi-Demand Forecasting
Experimental results demonstrate the effectiveness of the proposed system in accurately forecasting taxi demand, even in previously unobserved regions, thus showcasing its potential for optimizing taxi services and improving transportation efficiency on a broader scale.
Eco-Friendly Sensing for Human Activity Recognition
With the increasing number of IoT devices, there is a growing demand for energy-free sensors.
Privacy-Preserving by Design: Indoor Positioning System Using Wi-Fi Passive TDOA
Indoor localization systems have become increasingly important in a wide range of applications, including industry, security, logistics, and emergency services.
Privacy-Preserving Taxi-Demand Prediction Using Federated Learning
Taxi-demand prediction is an important application of machine learning that enables taxi-providing facilities to optimize their operations and city planners to improve transportation infrastructure and services.
Privacy-preserving Pedestrian Tracking using Distributed 3D LiDARs
In this paper, we introduce a novel privacy-preserving system for pedestrian tracking in smart environments using multiple distributed LiDARs of non-overlapping views.
Multi-task Learning for Concurrent Prediction of Thermal Comfort, Sensation, and Preference
To the best of our knowledge, this work is the first application of Multi-task Learning to thermal comfort prediction in classrooms.
