MONALISA 2.0 and the sea traffic management - a concept creating the need for new maritime information standards and software solutions

Postprint (published version

Location prediction and trajectory optimization in multi-UAV application missions

Unmanned aerial vehicles (a.k.a. drones) have a wide range of applications in e.g., aerial surveillance, mapping, imaging, monitoring, maritime operations, parcel delivery, and disaster response management. Their operations require reliable networking environments and location-based services in air-to-air links with cooperative drones, or air-to-ground links in concert with ground control stations. When equipped with high-resolution video cameras or sensors to gain environmental situation awareness through object detection/tracking, precise location predictions of individual or groups of drones at any instant possible is critical for continuous guidance. The location predictions then can be used in trajectory optimization for achieving efficient operations (i.e., through effective resource utilization in terms of energy or network bandwidth consumption) and safe operations (i.e., through avoidance of obstacles or sudden landing) within application missions. In this thesis, we explain a diverse set of techniques involved in drone location prediction, position and velocity estimation and trajectory optimization involving: (i) Kalman Filtering techniques, and (ii) Machine Learning models such as reinforcement learning and deep-reinforcement learning. These techniques facilitate the drones to follow intelligent paths and establish optimal trajectories while carrying out successful application missions under given resource and network constraints. We detail the techniques using two scenarios. The first scenario involves location prediction based intelligent packet transfer between drones in a disaster response scenario using the various Kalman Filtering techniques. The second scenario involves a learning-based trajectory optimization that uses various reinforcement learning models for maintaining high video resolution and effective network performance in a civil application scenario such as aerial monitoring of persons/objects. We conclude with a list of open challenges and future works for intelligent path planning of drones using location prediction and trajectory optimization techniques.Includes bibliographical references

INTEROPERABILITY FOR MODELING AND SIMULATION IN MARITIME EXTENDED FRAMEWORK

This thesis reports on the most relevant researches performed during the years of the Ph.D. at the Genova University and within the Simulation Team. The researches have been performed according to M&S well known recognized standards. The studies performed on interoperable simulation cover all the environments of the Extended Maritime Framework, namely Sea Surface, Underwater, Air, Coast & Land, Space and Cyber Space. The applications cover both the civil and defence domain. The aim is to demonstrate the potential of M&S applications for the Extended Maritime Framework, applied to innovative unmanned vehicles as well as to traditional assets, human personnel included. A variety of techniques and methodology have been fruitfully applied in the researches, ranging from interoperable simulation, discrete event simulation, stochastic simulation, artificial intelligence, decision support system and even human behaviour modelling

Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges

With the rapid development of marine activities, there has been an increasing number of maritime mobile terminals, as well as a growing demand for high-speed and ultra-reliable maritime communications to keep them connected. Traditionally, the maritime Internet of Things (IoT) is enabled by maritime satellites. However, satellites are seriously restricted by their high latency and relatively low data rate. As an alternative, shore & island-based base stations (BSs) can be built to extend the coverage of terrestrial networks using fourth-generation (4G), fifth-generation (5G), and beyond 5G services. Unmanned aerial vehicles can also be exploited to serve as aerial maritime BSs. Despite of all these approaches, there are still open issues for an efficient maritime communication network (MCN). For example, due to the complicated electromagnetic propagation environment, the limited geometrically available BS sites, and rigorous service demands from mission-critical applications, conventional communication and networking theories and methods should be tailored for maritime scenarios. Towards this end, we provide a survey on the demand for maritime communications, the state-of-the-art MCNs, and key technologies for enhancing transmission efficiency, extending network coverage, and provisioning maritime-specific services. Future challenges in developing an environment-aware, service-driven, and integrated satellite-air-ground MCN to be smart enough to utilize external auxiliary information, e.g., sea state and atmosphere conditions, are also discussed

Arctic Standards: Recommendations on Oil Spill Prevention, Response, and Safety in the U.S. Arctic Ocean

Oil spilled in Arctic waters would be particularly difficult to remove. Current technology has not been proved to effectively clean up oil when mixed with ice or when trapped under ice. An oil spill would have a profoundly adverse impact on the rich and complex ecosystem found nowhere else in the United States. The Arctic Ocean is home to bowhead, beluga, and gray whales; walruses; polar bears; and other magnificent marine mammals, as well as millions of migratory birds. A healthy ocean is important for these species and integral to the continuation of hunting and fishing traditions practiced by Alaska Native communities for thousands of years.To aid the United States in its efforts to modernize Arctic technology and equipment standards, this report examines the fierce Arctic conditions in which offshore oil and gas operations could take place and then offers a summary of key recommendations for the Interior Department to consider as it develops world-class, Arctic-specific regulatory standards for these activities. Pew's recommendations call for improved technology,equipment, and procedural requirements that match the challenging conditions in the Arctic and for full public participation and transparency throughout the decision-making process. Pew is not opposed to offshore drilling, but a balance must be achieved between responsible energy development and protection of the environment.It is essential that appropriate standards be in place for safety and for oil spill prevention and response in this extreme, remote, and vulnerable ecosystem. This report recommends updating regulations to include Arctic specific requirements and codifying temporary guidance into regulation. The appendixes to this report provide substantially more detail on the report's recommendations, including technical background documentation and additional referenced materials. Please refer to the full set of appendixes for a complete set of recommendations. This report and its appendixes offer guidelines for responsible hydrocarbon development in the U.S. Arctic Ocean

Communication and Control in Collaborative UAVs: Recent Advances and Future Trends

The recent progress in unmanned aerial vehicles (UAV) technology has significantly advanced UAV-based applications for military, civil, and commercial domains. Nevertheless, the challenges of establishing high-speed communication links, flexible control strategies, and developing efficient collaborative decision-making algorithms for a swarm of UAVs limit their autonomy, robustness, and reliability. Thus, a growing focus has been witnessed on collaborative communication to allow a swarm of UAVs to coordinate and communicate autonomously for the cooperative completion of tasks in a short time with improved efficiency and reliability. This work presents a comprehensive review of collaborative communication in a multi-UAV system. We thoroughly discuss the characteristics of intelligent UAVs and their communication and control requirements for autonomous collaboration and coordination. Moreover, we review various UAV collaboration tasks, summarize the applications of UAV swarm networks for dense urban environments and present the use case scenarios to highlight the current developments of UAV-based applications in various domains. Finally, we identify several exciting future research direction that needs attention for advancing the research in collaborative UAVs

Disentangling the resiliency of international transportation systems under uncertainty by a novel multi-layer spherical fuzzy decision-making framework:Evidence from an emerging economy

Although transportation systems play a critical role in the global socio-economic facets, they are acknowledged as vulnerable systems directly impacted by unexpected events, e.g., natural calamities, war, traffic accidents, terrorist attacks, and public health. In this respect, improving the resiliency of transportation systems under uncertainty is a controversial global challenge that this study could underpin. To do so, a systematic literature review (SLR) extracted a list of resiliency factors for resilient transportation systems. Next, a novel version of spherical fuzzy Delphi (SFD) screened factors, considering the case of Iran’s international maritime transportation system. Moreover, the causal network relationship of the finalised factors was analysed by a novel hybrid spherical fuzzy approach, including a decision-making trial and evaluation laboratory (DEMATEL) and the analytic network process (ANP). Later, the unexpected events that occurred after 2000 were investigated. The SLR deeply investigated 51 of the top relevant articles. As a result, 12 factors and 22 subfactors that affect transportation systems resiliency were extracted. Notably, the rest of the findings primarily apply to the Iranian context. By implementing the SFD, ten factors were screened for Iran’s international maritime transportation system and then analysed by SF-DEMATEL. After, the analysed factors were weighted by SFANP, where “recoverability” was selected as the most critical factor, and the “technological and communicational” factor was chosen as the least critical factor. Furthermore, the results provide a critical analysis of the policies adopted by Iran’s international maritime transportation system to enhance resiliency under disruptive events