NEMO: Internet of Things based Real-time Noise and Emissions MOnitoring System for Smart Cities

With the advent of ubiquitous sensors and Internet of Things (IoT) applications, research and development initiatives on smart cities are ramping up worldwide. It enables remote monitoring, management, and control of devices and the generation of fresh and actionable insight from huge quantities of real-time data. Real-time noise and emissions monitoring of vehicles remain indispensable in a smart city context. Effective management and control of noise and emissions of vehicles on the road are necessary and possible through analyzing lots of sensor data in real-time to take an actionable insight. To contribute to this, as part of an ongoing effort of the European Union project called ''NEMO: Noise and Emissions Monitoring and Radical Mitigation'', in this paper, we present the design and development of an IoT-based real-time noise and emissions monitoring system for vehicles in a smart city context. Real-world sensor data of the vehicles in some European cities are collected during the pilot tests. We have developed a complete application for infrastructure managers and analysts to monitor the sensor data related to noise and emissions of vehicles in real-time. The data of the individual road vehicles and trains in selected EU cities and from trains on a track in the Netherlands are collected in the cloud and analyzed with artificial intelligence (AI) algorithms for classification such as high emitter, medium emitter, and normal emitters. We present the development of a complete software solution that can be integrated with existing intelligent transportation systems in smart cities. Finally, we report the initial vehicle classification results from the Rotterdam (Netherlands) pilot test as a representative example for the NEMO monitoring system.acceptedVersio

Differential ZTD estimation based on high spatial resolution NWP data for the Nordic countries

This paper contains results from a study where Numerical Weather Product (NWP) data provided by MET Norway are used to estimate the differential zenith tropospheric delay (dZTD) for an area covering Scandinavia, Finland and the Baltic countries. The NWP data have a high spatial resolution of 2.5 × 2.5 km, and the estimated dZTD for the grid positions allow for calculation of the tropospheric gradient on short baselines. The results give an indication of how large dZTD values that can be observed for baselines up to 20 km, and where the largest events are located within the coverage area. The motivation for this investigation is to better understand the characteristics of this phenomena and how it might impact high precision and/or high integrity GNSS-based navigation systems in these regions.acceptedVersio

Secrecy Performance Analysis of Cooperative Nonorthogonal Multiple Access in IoT Networks

Different system models utilizing Non-orthogonal multiple access (NOMA) have been successfully studied to meet the growing capacity demands of the Internet of Things (IoT) devices for the next-generation networks. However, analyzing the anti-eavesdropping for NOMA systems under different scenarios and settings still needs further exploration before it can be practically deployed. Therefore, in this paper, we study the secrecy performance of a cooperative NOMA system in IoT networks where two source nodes communicate with their respective destination nodes via a common relay in the presence of an eavesdropper. Specifically, two source node sends their data in parallel over the same frequency band to the common relay node using uplink NOMA. Then, the relay node forwards the decoded symbols to the respective destination nodes using downlink NOMA in the presence of an eavesdropper. To enhance the security performance of the considered system, we study and propose an artificial noise (AN)-aided scheme in which the two destination nodes emit a jamming signal to confuse the eavesdropper while receiving the signal from the common relay node. We also study the effect of NOMA power allocation, perfect successive interference cancellation (pSIC), and imperfect SIC (ipSIC) on the considered system. Analytical expressions for the Ergodic capacity, Ergodic secrecy sum rate (ESSR), and secrecy outage probability (SOP) are mathematically derived and verified with the simulation results. Our results demonstrate that a significantly higher ESSR and lower SOP of the system can be attained compared to a conventional NOMA system without a destination-assisted jamming signal scheme.acceptedVersio

COROID: A Crowdsourcing-based Companion Drones to Tackle Current and Future Pandemics

Due to the current COVID-19 virus, which has already been declared a pandemic by the World Health Organization (WHO), we are witnessing the greatest pandemic of the decade. Millions of people are being infected, resulting in thousands of deaths every day across the globe. Even the world’s best healthcare-providing countries could not handle the pandemic because of the strain of treating thousands of patients at a time. The count of infections and deaths is increasing at an alarming rate because of the spread of the virus. We believe that innovative technologies could help reduce pandemics to a certain extent until we find a definite solution from the medical field to handle and treat such pandemic situations. Technology innovation has the potential to introduce new technologies that could support people and society during these difficult times. Therefore, this paper proposes the idea of using drones as a companion to tackle current and future pandemics. Our COROID drone is based on the principle of crowdsourcing sensors data of the public's smart devices, which can correlate the reading of the infrared cameras equipped on COROID drones. To the best of our knowledge, this concept has yet to be investigated either as a concept or as a product. Therefore, we believe that the COROID drone is innovative and has a huge potential to tackle COVID-19 and future pandemics.acceptedVersio

Extending sustainability from food to fashion consumption:the lived experience of working mothers

This report isa collection of the memos written in work package 1 of the LambdaRoad project, where the overall project objectives is to study the need and requirements for electronic communication (ecom) in the future transport system in Norway and develop a planning tool for ecom for the transport sector. lntroductory studies were performed in work package 1 and documented in this report. In particular we 1) have established va lue networks for ecom in Norway, 2) described the crucial terms in C-ITS ecom, including motivation for the planning tool, 3) established a comprehensive state of the art study for path loss models, a crucial part of the planning tool to be developed, 4) studied the literature to summarize the ecom requirements in the future transport system, and 5) conducted in-depth semi -structured interviews to reveal the requirements and needs of the planning tool in LambdaRoad for the project partners. Please note that some of the memos included might change during the rest of the project period, and that updates may occur

NEMO: Real-Time Noise and Exhaust Emissions Monitoring for Sustainable and Intelligent Transportation Systems

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.acceptedVersio

Federated Learning for Medical Applications: A Taxonomy, Current Trends, Challenges, and Future Research Directions

With the advent of the IoT, AI, ML, and DL algorithms, the landscape of data-driven medical applications has emerged as a promising avenue for designing robust and scalable diagnostic and prognostic models from medical data. This has gained a lot of attention from both academia and industry, leading to significant improvements in healthcare quality. However, the adoption of AI-driven medical applications still faces tough challenges, including meeting security, privacy, and quality of service (QoS) standards. Recent developments in \ac{FL} have made it possible to train complex machine-learned models in a distributed manner and have become an active research domain, particularly processing the medical data at the edge of the network in a decentralized way to preserve privacy and address security concerns. To this end, in this paper, we explore the present and future of FL technology in medical applications where data sharing is a significant challenge. We delve into the current research trends and their outcomes, unravelling the complexities of designing reliable and scalable \ac{FL} models. Our paper outlines the fundamental statistical issues in FL, tackles device-related problems, addresses security challenges, and navigates the complexity of privacy concerns, all while highlighting its transformative potential in the medical field. Our study primarily focuses on medical applications of \ac{FL}, particularly in the context of global cancer diagnosis. We highlight the potential of FL to enable computer-aided diagnosis tools that address this challenge with greater effectiveness than traditional data-driven methods. We hope that this comprehensive review will serve as a checkpoint for the field, summarizing the current state-of-the-art and identifying open problems and future research directions.Comment: Accepted at IEEE Internet of Things Journa

Compatibility Study in the AeroMACS Frequency Band

This paper contains results from compatibility studies between AeroMACS and other systems operating in the same or adjacent frequency bands. These systems are RLAN, AMT, MLS and FSS feeder links. For compatibility with the terrestrial systems, the minimum distance to interferer is calculated, i.e. the minimum distance an interfering transmitter can be from a victim receiver without degrading the system performance beyond a permitted limit. For compatibility with FSS feeder links, the number of AeroMACS systems that may be installed in Europe without causing harmful interference to non-GEO satellite feeder link receivers is calculated. The results presented in this paper indicate that both MLS and AMT may cause harmful interference to AeroMACS if no precautions are made, while this is unlikely to happen when it comes to RLANs. Concerning compatibility with FSS feeder links, more than about 400 airports in Europe must be equipped with large AeroMACS installations to potentially cause harmful interference to FSS systems

User Requirements for HEO SATCOM for ATM in High Latitudes

It is currently a significant ongoing effort worldwide to develop the future Air Traffic Management (ATM) system. As part of this work, a satellite communication system may ease the congestion problem for ATM services in high density airspace, and in addition provide coverage in oceanic, remote and polar (ORP) areas. For coverage over polar areas, satellites in highly elliptical orbits (HEO) are particularly suitable. In this paper, an overview of user categories is given and the channel characteristics of an aeronautical satellite channel are considered. Both Molniya and Tundra orbits are included. Curves show how parameters like elevation angle, free space path loss and Doppler shift vary as function of satellite movements. In addition, atmospheric effects due to signal propagation through the ionosphere and the troposphere is considered, and finally the effect of multipath propagation due to signal reflections by the aircraft surface and ground.User Requirements for HEO SATCOM for ATM in High Latitude

Communication for Air Traffic Management (ATM) in Northern Areas

It is currently a significant ongoing effort worldwide to develop the future Air Traffic Management (ATM) system. As part of this work, a satellite communication system may ease the congestion problem for ATM services in high density airspace, and in addition provide coverage in oceanic, remote and polar (ORP) areas. For coverage over polar areas, satellites in highly elliptical orbits (HEO) are particularly suitable. In this paper the channel characteristics of an aeronautical satellite channel is considered. Both Molniya and Tundra orbits are included. Curves show how parameters like elevation angle, free space path loss and Doppler shift vary as function of satellite movements. In addition, atmospheric effects due to signal propagation through the ionosphere and the troposphere is considered, and finally the effect of multipath propagation due to signal reflections by the aircraft surface and ground.Communication for Air Traffic Management (ATM) in Northern Area