Enabling technologies and sustainable smart cities

The technological interventions in everyday processes has led to the rise of Smart ecosystems where all aspects of everyday life like governance, transportation, agriculture, logistics, maintenance, education and healthcare are automated in some way or the other and can be controlled, managed and accessed remotely with the help of smart devices. This has led to the concept of Smart cities where Information Communication and Technology (ICT) is merged with the existing traditional infrastructure of a city which is then coordinated and managed using digital technology. This idea of smart cities is slowly but surely coming into reality as many countries around the globe are adopting this idea and coming up with their own model of smart cities. At the core of smart city lies the sensors and actuators embedded in the smart devices that sense the environment for facilitating effective decision making. The microcontrollers available in these devices are programmed to take decisions automatically based on the information received from the sensors. This involves integration of several information and communication technologies like artificial intelligence, protocols, Internet of things (IoT), wireless sensor network (WSN) etc. This paper discusses and extensively reviews the role of enabling technologies in smart cities. The paper further highlights the challenges and limitations in the development of smart cities along with the mitigation strategies. Specifically, three categories of challenges are identified namely technical, socio-economic and environmental giving specifics of each category. Finally, some of the best practices for attaining sustainable smart cities are provided.5311-8814-F0ED | Sara Maria da Cruz Maia de Oliveira PaivaN/

Towards Automated Urban Planning: When Generative and ChatGPT-like AI Meets Urban Planning

The two fields of urban planning and artificial intelligence (AI) arose and developed separately. However, there is now cross-pollination and increasing interest in both fields to benefit from the advances of the other. In the present paper, we introduce the importance of urban planning from the sustainability, living, economic, disaster, and environmental perspectives. We review the fundamental concepts of urban planning and relate these concepts to crucial open problems of machine learning, including adversarial learning, generative neural networks, deep encoder-decoder networks, conversational AI, and geospatial and temporal machine learning, thereby assaying how AI can contribute to modern urban planning. Thus, a central problem is automated land-use configuration, which is formulated as the generation of land uses and building configuration for a target area from surrounding geospatial, human mobility, social media, environment, and economic activities. Finally, we delineate some implications of AI for urban planning and propose key research areas at the intersection of both topics.Comment: TSAS Submissio

The case of Ferbritas Cadastre Information System

The processes of mobilization of land for infrastructures of public and private domain are developed according to proper legal frameworks and systematically confronted with the impoverished national situation as regards the cadastral identification and regularization, which leads to big inefficiencies, sometimes with very negative impact to the overall effectiveness. This project report describes Ferbritas Cadastre Information System (FBSIC) project and tools, which in conjunction with other applications, allow managing the entire life-cycle of Land Acquisition and Cadastre, including support to field activities with the integration of information collected in the field, the development of multi-criteria analysis information, monitoring all information in the exploration stage, and the automated generation of outputs. The benefits are evident at the level of operational efficiency, including tools that enable process integration and standardization of procedures, facilitate analysis and quality control and maximize performance in the acquisition, maintenance and management of registration information and expropriation (expropriation projects). Therefore, the implemented system achieves levels of robustness, comprehensiveness, openness, scalability and reliability suitable for a structural platform. The resultant solution, FBSIC, is a fit-for-purpose cadastre information system rooted in the field of railway infrastructures. FBSIC integrating nature of allows: to accomplish present needs and scale to meet future services; to collect, maintain, manage and share all information in one common platform, and transform it into knowledge; to relate with other platforms; to increase accuracy and productivity of business processes related with land property management

GeoCoin:supporting ideation and collaborative design with location-based smart contracts

Design and HCI researchers are increasingly working with complex digital infrastructures, such as cryptocurrencies, distributed ledgers and smart contracts. These technologies will have a profound impact on digital systems and their audiences. However, given their emergent nature and technical complexity, involving non-specialists in the design of applications that employ these technologies is challenging. In this paper, we discuss these challenges and present GeoCoin, a location-based platform for embodied learning and speculative ideating with smart contracts. In collaborative workshops with GeoCoin, participants engaged with location-based smart contracts, using the platform to explore digital `debit' and `credit' zones in the city. These exercises led to the design of diverse distributed-ledger applications, for time-limited financial unions, participatory budgeting, and humanitarian aid. These results contribute to the HCI community by demonstrating how an experiential prototype can support understanding of the complexities behind new digital infrastructures and facilitate participant engagement in ideation and design processes

An Emerging Decision Support Systems Technology for Disastrous Actions Management

The purpose of the chapter is to introduce a conceptual approach of emerging decision \ud \ud support systems (DSS) development in enhancing contextual support in decision making. \ud \ud We analyse the requirements of outlining a technological solution model for addressing \ud \ud disaster management problem situations in which decision makers at different levels can \ud \ud have the information support to respond effectively

External monitoring changes in vehicle hardware profiles: enhancing automotive cyber-security

As the vehicles are gradually transformed into the connected-vehicles, standard features of the past (i.e., immobilizer, keyless entry, self-diagnostics) were neglected to be software updated and hardware upgraded so they do not 'align” with the cyber-security demands of the new ICT era (IoT, Industry 4.0, IPv6, sensor technology) we have stepped into, therefore introducing critical legacy IT security issues. Stepping beyond the era of common auto-theft and 'chop-shops,” the new wave of attackers have cyber-skills to exploit these vulnerabilities and steal the vehicle or manipulate it. Recent evolution in ICT offered automotive industry vital tools for vehicle safety, functionality and up to 2010, theft prevention. However, the same technologies are the ones that make vehicles prone to cyber-attacks. To counter such attacks, this work proposes a unified solution that logs all hardware profile changes of a vehicle in a blockchain, to manage control and allow only authenticated changes, subject to user, time, geospatial, and contextual constraints exploiting several blockchain features. Testing of the proposed solution omens the prevention of numerous commons attacks, while additionally providing forensics capabilities and significantly enhancing the security architecture of the vehicle (respecting the original IT architectural design of automotive manufacturers)