Empowering citizens' cognition and decision making in smart sustainable cities

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Advances in Internet technologies have made it possible to gather, store, and process large quantities of data, often in real time. When considering smart and sustainable cities, this big data generates useful information and insights to citizens, service providers, and policy makers. Transforming this data into knowledge allows for empowering citizens' cognition as well as supporting decision-making routines. However, several operational and computing issues need to be taken into account: 1) efficient data description and visualization, 2) forecasting citizens behavior, and 3) supporting decision making with intelligent algorithms. This paper identifies several challenges associated with the use of data analytics in smart sustainable cities and proposes the use of hybrid simulation-optimization and machine learning algorithms as an effective approach to empower citizens' cognition and decision making in such ecosystemsPeer ReviewedPostprint (author's final draft

A Mission Coordinator Approach for a Fleet of UAVs in Urban Scenarios

Abstract The use of Unmanned Aerial Vehicles (UAVs) is now common, but although they have been for various applications, there are still a lot of challenges that need to be overcome. One key issue is related to standardizing the use of these vehicles in urban environments and guaranteeing a minimum risk level for the population. To rise to these challenges, autonomous strategies that optimize and coordinate vehicles in cooperative missions and avoid human operators should be developed. The novelty of this paper is the development of an autonomous urban mission coordinator, which is responsible for the high-level logistics of a fleet of heterogeneous vehicles. A multi-variable weighted algorithm based on a tree optimization method is also proposed

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

AUTONOMOUS SYSTEMS & SAFETY ISSUES: THE ROADMAP TO ENABLE NEW ADVANCES IN INDUSTRIAL APPLICATIONS

The paper addresses the safety issues related to the development of new solutions based on autonomous systems for industrial applications and the necessity to develop experimental environments for investigating these cases; a set of examples is proposed in order to provide cases and challenges as well as to suggest approaches to address these problems

UAV-CLOUD: A PLATFORM FOR UAV RESOURCES AND SERVICES ON THE CLOUD

UAVs - Unmanned Aerial Vehicles – have gained significant attention recently, due to the increasingly growing range of applications. However, developing collaborative UAV applications using traditional technologies in a tightly coupled design requires a great deal of development effort, time, and budget especially for heterogeneous UAVs. Moreover, monitoring and accessing UAV resources using traditional communication media suffer from several restrictions and limitations. This research aims to simplify the efforts, reduce the time, and lower the costs of developing collaborative applications for distributed heterogeneous UAVs. In addition, the research aims to provide ubiquitous UAV resources access. A platform is proposed for developing distributed UAVs. This platform provides services to simplify application development. In this approach, UAVs are integrated with the Cloud Computing paradigm to provide ubiquitous access to their resources and services. Due to the limited capabilities of UAVs, a lightweight architecture is adopted. UAV resources and services are modeled in a Resource Oriented Architecture which is a new flexible web service design pattern with loosely coupled interaction between services. Hence, they are accessed as Representational State Transfer RESTful services using HTTP. Moreover, the research proposes using a broker architecture to increase efficiency by separating responsibilities. Therefore, it separates the requester’s logic and functionalities from the provider’s. It also takes the responsibility for allocating the issued request to the available and suitable UAV(s). To test the proposed platform, I first developed the UAV resources as a payload subsystem then provided them with Internet connectivity. Then, resource identifiers and uniform interfaces were developed using the RESTful Application Programming Interfaces (APIs). I also developed the broker service along with a database containing the information of the registered UAVs and their resources. The platform system components were tested using a requester interface in a browser by issuing a request for a resource to the broker to find and request the service from a suitable UAV. The test was done for retrieving data from UAVs as well as requesting actions from them. The main contributions of this research are proposing the UAV-Cloud platform for simplifying the development of ubiquitous UAV applications and its vii perspectives, as well as a lightweight loosely coupled design for UAV resources. Another contribution is developing the broker architecture for separating responsibilities in this platform

TCitySmartF: A comprehensive systematic framework for transforming cities into smart cities

A shared agreed-upon definition of "smart city" (SC) is not available and there is no "best formula" to follow in transforming each and every city into SC. In a broader inclusive definition, it can be described as an opportunistic concept that enhances harmony between the lives and the environment around those lives perpetually in a city by harnessing the smart technology enabling a comfortable and convenient living ecosystem paving the way towards smarter countries and the smarter planet. SCs are being implemented to combine governors, organisations, institutions, citizens, environment, and emerging technologies in a highly synergistic synchronised ecosystem in order to increase the quality of life (QoL) and enable a more sustainable future for urban life with increasing natural resource constraints. In this study, we analyse how to develop citizen- and resource-centric smarter cities based on the recent SC development initiatives with the successful use cases, future SC development plans, and many other particular SC development solutions. The main features of SC are presented in a framework fuelled by recent technological advancement, particular city requirements and dynamics. This framework - TCitySmartF 1) aims to aspire a platform that seamlessly forges engineering and technology solutions with social dynamics in a new philosophical city automation concept - socio-technical transitions, 2) incorporates many smart evolving components, best practices, and contemporary solutions into a coherent synergistic SC topology, 3) unfolds current and future opportunities in order to adopt smarter, safer and more sustainable urban environments, and 4) demonstrates a variety of insights and orchestrational directions for local governors and private sector about how to transform cities into smarter cities from the technological, social, economic and environmental point of view, particularly by both putting residents and urban dynamics at the forefront of the development with participatory planning and interaction for the robust community- and citizen-tailored services. The framework developed in this paper is aimed to be incorporated into the real-world SC development projects in Lancashire, UK

Supporting UAVs with Edge Computing: A Review of Opportunities and Challenges

Over the last years, Unmanned Aerial Vehicles (UAVs) have seen significant advancements in sensor capabilities and computational abilities, allowing for efficient autonomous navigation and visual tracking applications. However, the demand for computationally complex tasks has increased faster than advances in battery technology. This opens up possibilities for improvements using edge computing. In edge computing, edge servers can achieve lower latency responses compared to traditional cloud servers through strategic geographic deployments. Furthermore, these servers can maintain superior computational performance compared to UAVs, as they are not limited by battery constraints. Combining these technologies by aiding UAVs with edge servers, research finds measurable improvements in task completion speed, energy efficiency, and reliability across multiple applications and industries. This systematic literature review aims to analyze the current state of research and collect, select, and extract the key areas where UAV activities can be supported and improved through edge computing