A Smart Waste Management System Framework Using IoT and LoRa for Green City Project

Waste management is a pressing concern for society, requiring substantial labor resources and impacting various social aspects. Green cities strive for achieving a net zero-carbon footprint, including efficient waste management. The waste management system deals with three problems that are interrelated: a) the timely checking of the status of bins to prevent overflow; b) checking the precise location of bins; and c) finding the optimal route to the filled bins. The existing systems fail to satisfy all three problem areas with a single solution. To track the overflow of the bin, the proposed model uses ultrasonic sensors, which are complemented with LoRa to transmit the exact location of the bins in a real-time environment. The existing models are not that efficient at calculating the exact bin-filled status along with the precise location of the bins. The Floyd-Warshall algorithm in the proposed model optimizes waste collection using the Floyd-Warshall algorithm to determine the shortest path. Leveraging low-cost IoT technologies, specifically LoRa modules for data transfer, our solution offers benefits such as simplicity, affordability, and ease of replacement. By employing the Floyd-Warshall algorithm with a time complexity of O (n^3), our method efficiently determines the most optimal waste pickup route, saving time and resources. This study presents a smart waste management solution utilising Arduino UNO microcontrollers, ultrasonic sensors, and LoRaWAN to measure waste levels accurately. The proposed strategy aims to create clean and pollution-free cities by addressing the problem of waste distribution caused by poor collection techniques

Risk Analysis for Smart Cities Urban Planners: Safety and Security in Public Spaces

Christopher Alexander in his famous writings "The Timeless Way of Building" and "A pattern language" defined a formal language for the description of a city. Alexander developed a generative grammar able to formally describe complex and articulated concepts of architecture and urban planning to define a common language that would facilitate both the participation of ordinary citizens and the collaboration between professionals in architectural and urban planning. In this research, a similar approach has been applied to let two domains communicate although they are very far in terms of lexicon, methodologies and objectives. These domains are urban planning, urban design and architecture, seen as the first domain both in terms of time and in terms of completeness of vision, and the one relating to the world of engineering, made by innumerable disciplines. In practice, there is a domain that defines the requirements and the overall vision (the first) and a domain (the second) which implements them with real infrastructures and systems. To put these two worlds seamlessly into communication, allowing the concepts of the first world to be translated into those of the second, Christopher Alexander’s idea has been followed by defining a common language. By applying Essence, the software engineering formal descriptive theory, using its customization rules, to the concept of a Smart City, a common language to completely trace the requirements at all levels has been defined. Since the focus was on risk analysis for safety and security in public spaces, existing risk models have been considered, evidencing a further gap also within the engineering world itself. Depending on the area being considered, risk management models have different and siloed approaches which ignore the interactions of one type of risk with the others. To allow effective communication between the two domains and within the engineering domain, a unified risk analysis framework has been developed. Then a framework (an ontology) capable of describing all the elements of a Smart City has been developed and combined with the common language to trace the requirements. Following the philosophy of the Vienna Circle, a creative process called Aufbau has then been defined to allow the generation of a detailed description of the Smart City, at any level, using the common language and the ontology above defined. Then, the risk analysis methodology has been applied to the city model produced by Aufbau. The research developed tools to apply such results to the entire life cycle of the Smart City. With these tools, it is possible to understand how much a given architectural, urban planning or urban design requirement is operational at a given moment. In this way, the narration can accurately describe how much the initial requirements set by architects, planners and urban designers and, above all, the values required by stakeholders, are satisfied, at any time. The impact of this research on urban planning is the ability to create a single model between the two worlds, leaving everyone free to express creativity and expertise in the appropriate forms but, at the same time, allowing both to fill the communication gap existing today. This new way of planning requires adequate IT tools and takes the form, from the engineering side, of harmonization of techniques already in use and greater clarity of objectives. On the side of architecture, urban planning and urban design, it is instead a powerful decision support tool, both in the planning and operational phases. This decision support tool for Urban Planning, based on the research results, is the starting point for the development of a meta-heuristic process using an evolutionary approach. Consequently, risk management, from Architecture/Urban Planning/Urban Design up to Engineering, in any phase of the Smart City’s life cycle, is seen as an “organism” that evolves.Christopher Alexander nei suoi famosi scritti "The Timeless Way of Building" e "A pattern language" ha definito un linguaggio formale per la descrizione di una città, sviluppando una grammatica in grado di descrivere formalmente concetti complessi e articolati di architettura e urbanistica, definendo un linguaggio comune per facilitare la partecipazione dei comuni cittadini e la collaborazione tra professionisti. In questa ricerca, un approccio simile è stato applicato per far dialogare due domini sebbene siano molto distanti in termini di lessico, metodologie e obiettivi. Essi sono l'urbanistica, l'urban design e l'architettura, visti come primo dominio sia in termini di tempo che di completezza di visione, e quello del mondo dell'ingegneria, con numerose discipline. In pratica, esiste un dominio che definisce i requisiti e la visione d'insieme (il primo) e un dominio (il secondo) che li implementa con infrastrutture e sistemi reali. Per metterli in perfetta comunicazione, permettendo di tradurre i concetti del primo in quelli del secondo, si è seguita l'idea di Alexander definendo un linguaggio. Applicando Essence, la teoria descrittiva formale dell'ingegneria del software al concetto di Smart City, è stato definito un linguaggio comune per tracciarne i requisiti a tutti i livelli. Essendo il focus l'analisi dei rischi per la sicurezza negli spazi pubblici, sono stati considerati i modelli di rischio esistenti, evidenziando un'ulteriore lacuna anche all'interno del mondo dell'ingegneria stessa. A seconda dell'area considerata, i modelli di gestione del rischio hanno approcci diversi e isolati che ignorano le interazioni di un tipo di rischio con gli altri. Per consentire una comunicazione efficace tra i due domini e all'interno del dominio dell'ingegneria, è stato sviluppato un quadro di analisi del rischio unificato. Quindi è stato sviluppato un framework (un'ontologia) in grado di descrivere tutti gli elementi di una Smart City e combinato con il linguaggio comune per tracciarne i requisiti. Seguendo la filosofia del Circolo di Vienna, è stato poi definito un processo creativo chiamato Aufbau per consentire la generazione di una descrizione dettagliata della Smart City, a qualsiasi livello, utilizzando il linguaggio comune e l'ontologia sopra definita. Infine, la metodologia dell'analisi del rischio è stata applicata al modello di città prodotto da Aufbau. La ricerca ha sviluppato strumenti per applicare tali risultati all'intero ciclo di vita della Smart City. Con questi strumenti è possibile capire quanto una data esigenza architettonica, urbanistica o urbanistica sia operativa in un dato momento. In questo modo, la narrazione può descrivere con precisione quanto i requisiti iniziali posti da architetti, pianificatori e urbanisti e, soprattutto, i valori richiesti dagli stakeholder, siano soddisfatti, in ogni momento. L'impatto di questa ricerca sull'urbanistica è la capacità di creare un modello unico tra i due mondi, lasciando ognuno libero di esprimere creatività e competenza nelle forme appropriate ma, allo stesso tempo, permettendo ad entrambi di colmare il gap comunicativo oggi esistente. Questo nuovo modo di progettare richiede strumenti informatici adeguati e si concretizza, dal lato ingegneristico, in un'armonizzazione delle tecniche già in uso e in una maggiore chiarezza degli obiettivi. Sul versante dell'architettura, dell'urbanistica e del disegno urbano, è invece un potente strumento di supporto alle decisioni, sia in fase progettuale che operativa. Questo strumento di supporto alle decisioni per la pianificazione urbana, basato sui risultati della ricerca, è il punto di partenza per lo sviluppo di un processo meta-euristico utilizzando un approccio evolutivo

Mobile Phone-Based Artificial Intelligence Development for Maintenance Asset Management

22-8099Transportation asset management needs timely information collection to inform relevant maintenance practices (e.g., resource planning). Traditional data collection methods in transportation asset management require either manual operation or support of unique equipment (e.g., Light Detection and Ranging (LiDAR)), which could be labor-intensive or costly to implement. With the advancement of computing techniques, artificial intelligence (AI) has been developed to be capable of automatically detecting objects in images and videos. In this project, we developed accurate and efficient AI algorithms to automatically collect and analyze transportation asset status, including identification of pavement marking issues, traffic signs, litter & trash, and steel guardrails & concrete barriers. The AI algorithms were developed based on the You Only Look Once (YOLO) framework built on Convolution Neural Network as the deep learning algorithms. Specifically, a smartphone was mounted on the vehicle\u2019s front windshield to collect videos of transportation assets on both highways and local roads. These videos were then converted and processed into labeled images to be training and test datasets for AI algorithm training. Then, AI models were developed for automatic object detection of the listed transportation assets above. The results demonstrate that the developed AI models achieve good performance in identifying targeted objects with over 85% accuracy. The developed AI package is expected to enable timely and efficient information collection of transportation assets, hence, improving road safety

A systematic literature review on Virtual Reality and Augmented Reality in terms of privacy, authorization and data-leaks

In recent years, VR and AR has exploded into a multimillionaire market. As this emerging technology has spread to a variety of businesses and is rapidly increasing among users. It is critical to address potential privacy and security concerns that these technologies might pose. In this study, we discuss the current status of privacy and security in VR and AR. We analyse possible problems and risks. Besides, we will look in detail at a few of the major concerns issues and related security solutions for AR and VR. Additionally, as VR and AR authentication is the most thoroughly studied aspect of the problem, we concentrate on the research that has already been done in this area.Comment: 9 Pages, 4 figure

Green Cities Artificial Intelligence

119 pagesIn an era defined by rapid urbanization, the effective planning and management of cities have become paramount to ensure sustainable development, efficient resource allocation, and enhanced quality of life for residents. Traditional methods of urban planning and management are grappling with the complexities and challenges presented by modern cities. Enter Artificial Intelligence (AI), a disruptive technology that holds immense potential to revolutionize the way cities are planned, designed, and operated. The primary aim of this report is to provide an in-depth exploration of the multifaceted role that Artificial Intelligence plays in modern city planning and management. Through a comprehensive analysis of key AI applications, case studies, challenges, and ethical considerations, the report aims to provide resources for urban planners, City staff, and elected officials responsible for community planning and development. These include a model City policy, draft informational public meeting format, AI software and applications, implementation actions, AI timeline, glossary, and research references. This report represents the cumulative efforts of many participants and is sponsored by the City of Salem and Sustainable City Year Program. The Green Cities AI project website is at: https://blogs.uoregon.edu/artificialintelligence/. As cities continue to evolve into complex ecosystems, the integration of Artificial Intelligence stands as a pivotal force in shaping their trajectories. Through this report, we aim to provide a comprehensive understanding of how AI is transforming the way cities are planned, operated, and experienced. By analyzing the tools, applications, and ethical considerations, we hope to equip policymakers, urban planners, and stakeholders with the insights needed to navigate the AI-driven urban landscape effectively and create cities that are not only smart but also sustainable, resilient, and regenerative.This year's SCYP partnership is possible in part due to support from U.S. Senators Ron Wyden and Jeff Merkley, as well as former Congressman Peter DeFazio, who secured federal funding for SCYP through Congressionally Directed Spending. With additional funding from the city of Salem, the partnerships will allow UO students and faculty to study and make recommendations on city-identified projects and issues

Harnessing the power of the general public for crowdsourced business intelligence: a survey

International audienceCrowdsourced business intelligence (CrowdBI), which leverages the crowdsourced user-generated data to extract useful knowledge about business and create marketing intelligence to excel in the business environment, has become a surging research topic in recent years. Compared with the traditional business intelligence that is based on the firm-owned data and survey data, CrowdBI faces numerous unique issues, such as customer behavior analysis, brand tracking, and product improvement, demand forecasting and trend analysis, competitive intelligence, business popularity analysis and site recommendation, and urban commercial analysis. This paper first characterizes the concept model and unique features and presents a generic framework for CrowdBI. It also investigates novel application areas as well as the key challenges and techniques of CrowdBI. Furthermore, we make discussions about the future research directions of CrowdBI

Human Digital Twin: A Survey

Digital twin has recently attracted growing attention, leading to intensive research and applications. Along with this, a new research area, dubbed as "human digital twin" (HDT), has emerged. Similar to the conception of digital twin, HDT is referred to as the replica of a physical-world human in the digital world. Nevertheless, HDT is much more complicated and delicate compared to digital twins of any physical systems and processes, due to humans' dynamic and evolutionary nature, including physical, behavioral, social, physiological, psychological, cognitive, and biological dimensions. Studies on HDT are limited, and the research is still in its infancy. In this paper, we first examine the inception, development, and application of the digital twin concept, providing a context within which we formally define and characterize HDT based on the similarities and differences between digital twin and HDT. Then we conduct an extensive literature review on HDT research, analyzing underpinning technologies and establishing typical frameworks in which the core HDT functions or components are organized. Built upon the findings from the above work, we propose a generic architecture for the HDT system and describe the core function blocks and corresponding technologies. Following this, we present the state of the art of HDT technologies and applications in the healthcare, industry, and daily life domain. Finally, we discuss various issues related to the development of HDT and point out the trends and challenges of future HDT research and development