Abstract
Research and development efforts on sustainable and intelligent transportation systems are accelerating globally as the transportation sector contributes significantly to environmental pollution and produces a variety of noise and emissions that impact the climate. With the emergence of ubiquitous sensors and Internet of Things (IoT) applications, finding innovative transport solutions, including adequate climate change mitigation, will all be vital components of a sustainable transport future. Thus, it is essential to continuously monitor noise and exhaust emissions from road vehicles, trains, and ships. As a contribution to addressing this as part of an effort of the European Union project called “NEMO: Noise and Emissions Monitoring and Radical Mitigation", in this paper, we propose the design and development of a real-time noise and exhaust emissions monitoring for sustainable and intelligent transportation systems. We report real-world field testing in some European cities where vehicle noise and exhaust emissions data are gathered in the cloud-enabled Nautilus platform and evaluated using artificial intelligence (AI) algorithms to determine their categorization into different classes of emitters and thereby enabling the infrastructure managers to define logic and actions to be taken by high emitters in near real-time. We outline the creation of a complete NEMO solution to monitor and reduce noise and emissions in real time for sustainable and intelligent transportation systems.