Scan to BIM for 3D reconstruction of the papal basilica of saint Francis in Assisi In Italy

The historical building heritage, present in the most of Italian cities centres, is, as part of the construction sector, a working potential, but unfortunately it requires planning of more complex and problematic interventions. However, policies to support on the existing interventions, together with a growing sensitivity for the recovery of assets, determine the need to implement specific studies and to analyse the specific problems of each site. The purpose of this paper is to illustrate the methodology and the results obtained from integrated laser scanning activity in order to have precious architectural information useful not only from the cultural heritage point of view but also to construct more operative and powerful tools, such as BIM (Building Information Modelling) aimed to the management of this cultural heritage. The Papal Basilica and the Sacred Convent of Saint Francis in Assisi in Italy are, in fact, characterized by unique and complex peculiarities, which require a detailed knowledge of the sites themselves to ensure visitor’s security and safety. For such a project, we have to take in account all the people and personnel normally present in the site, visitors with disabilities and finally the needs for cultural heritage preservation and protection. This aim can be reached using integrated systems and new technologies, such as Internet of Everything (IoE), capable of connecting people, things (smart sensors, devices and actuators; mobile terminals; wearable devices; etc.), data/information/knowledge and processes to reach the desired goals. The IoE system must implement and support an Integrated Multidisciplinary Model for Security and Safety Management (IMMSSM) for the specific context, using a multidisciplinary approach

An IoE Blockchain-Based Network Knowledge Management Model for Resilient Disaster Frameworks

The disaster area is a constantly changing environment, which can make it challenging to distribute supplies effectively. The lack of accurate information about the required goods and potential bottlenecks in the distribution process can be detrimental. The success of a response network is dependent on collaboration, coordination, sovereignty, and equal distribution of relief resources. To facilitate these interactions and improve knowledge of supply chain operations, a reliable and dynamic logistic system is essential. This study proposes the integration of blockchain technology, the Internet of Things (IoT), and the Internet of Everything (IoE) into the disaster management structure. The proposed disaster response model aims to reduce response times and ensure the secure and timely distribution of goods. The hyper-connected disaster supply network is modeled through a concrete implementation on the Network Simulation (NS2) platform. The simulation results demonstrate that the proposed method yields significant improvements in several key performance metrics. Specifically, it achieved more than a 30% improvement in the successful migration of tasks, a 17% reduction in errors, a 15% reduction in delays, and a 9% reduction in energy consumption

A Semantic loT Early Warning System for Natural Environment Crisis Management

An early warning system (EWS) is a core type of data driven Internet of Things (IoTs) system used for environment disaster risk and effect management. The potential benefits of using a semantic-type EWS include easier sensor and data source plug-and-play, simpler, richer, and more dynamic metadata-driven data analysis and easier service interoperability and orchestration. The challenges faced during practical deployments of semantic EWSs are the need for scalable time-sensitive data exchange and processing (especially involving heterogeneous data sources) and the need for resilience to changing ICT resource constraints in crisis zones. We present a novel IoT EWS system framework that addresses these challenges, based upon a multisemantic representation model.We use lightweight semantics for metadata to enhance rich sensor data acquisition.We use heavyweight semantics for top level W3CWeb Ontology Language ontology models describing multileveled knowledge-bases and semantically driven decision support and workflow orchestration. This approach is validated through determining both system related metrics and a case study involving an advanced prototype system of the semantic EWS, integrated with a reployed EWS infrastructure

Review—Machine Learning Techniques in Wireless Sensor Network Based Precision Agriculture

The use of sensors and the Internet of Things (IoT) is key to moving the world\u27s agriculture to a more productive and sustainable path. Recent advancements in IoT, Wireless Sensor Networks (WSN), and Information and Communication Technology (ICT) have the potential to address some of the environmental, economic, and technical challenges as well as opportunities in this sector. As the number of interconnected devices continues to grow, this generates more big data with multiple modalities and spatial and temporal variations. Intelligent processing and analysis of this big data are necessary to developing a higher level of knowledge base and insights that results in better decision making, forecasting, and reliable management of sensors. This paper is a comprehensive review of the application of different machine learning algorithms in sensor data analytics within the agricultural ecosystem. It further discusses a case study on an IoT based data-driven smart farm prototype as an integrated food, energy, and water (FEW) system

AI Enabled-6G: Artificial Intelligence (AI) for Integration of 6G Wireless Communications

The research in wireless communication is rapidly shifting to the next generation mobile system, 6G. Fifth-generation mobile network standards are now in use. However, there are still some user criteria that are expected to be satisfied in the sixth-generation communication network. 6G is estimated to enable the unprecedented intelligence Internet of Things with extremely varied stimulating necessities. Currently, artificial intelligence (AI) is considered as a novel paradigm for the designing and optimizing intelligent 6G architectures, standards and functions. By 2030, all of the people would be using 6G. In this paper, we investigate 6G trends, requirements, challenges & potential solutions and how AI-enabled technique can integrate 6G communications. The analysis section provides the need and how AI-empowered technique efficiently and effectively enhances the performance of network. The 6G networks based on intelligent AI architecture used to understand automatic network adjustment, knowledge discovery, intelligent service provisioning, and smart resource management

Prevention of Falls from Heights in Construction Using an IoT System Based on Fuzzy Markup Language and JFML

The main cause of fatal accidents in the construction sector are falls from height (FFH) and the inappropriate use of a harness is commonly associated with these fatalities. Traditional methods, such as onsite inspections, safety communication, or safety training, are not enough to mitigate accidents caused by FFH associated with a poor management in the use of a harness. Although some technological solutions for the automated monitoring of workers could improve safety conditions, their use is not frequent due to the particularities of construction sites: complexity, dynamic environments, outdoor workplaces, etc. Then, the integration of expert knowledge with technology is a key issue. Fuzzy logic systems (FLS) and Internet of Things (IoT) present many potential benefits, such as real-time decisions being made based on FLS and data from sensors. In the current research, the development and test of an IoT system integrated with the Java Fuzzy Markup Language Library for FLS, to support experts’ decision making in FFH, is proposed. The proposal was checked in four construction scenarios based on working conditions with different levels of risk of FFH and obtained promising results.Universidad de Malaga Plan Propio-Universidad de MalagaSpanish GovernmentEuropean Commission RTI2018-098371-B-I0

Prevention of Falls from Heights in Construction Using an IoT System Based on Fuzzy Markup Language and JFML

The main cause of fatal accidents in the construction sector are falls from height (FFH) and the inappropriate use of a harness is commonly associated with these fatalities. Traditional methods, such as onsite inspections, safety communication, or safety training, are not enough to mitigate accidents caused by FFH associated with a poor management in the use of a harness. Although some technological solutions for the automated monitoring of workers could improve safety conditions, their use is not frequent due to the particularities of construction sites: complexity, dynamic environments, outdoor workplaces, etc. Then, the integration of expert knowledge with technology is a key issue. Fuzzy logic systems (FLS) and Internet of Things (IoT) present many potential benefits, such as real-time decisions being made based on FLS and data from sensors. In the current research, the development and test of an IoT system integrated with the Java Fuzzy Markup Language Library for FLS, to support experts’ decision making in FFH, is proposed. The proposal was checked in four construction scenarios based on working conditions with different levels of risk of FFH and obtained promising results

For Better or Worse : Imagining Innovation in Smart City Municipal Design

The smart city concept recently (ca. 2010) emerged as a corporate-led system-as-a-service (SaaS) tool to meet city needs of accessibility and efficiency. I looked at three Western cities—Reykjavík, San José, and Toronto—to discover what it meant for city managers to meet municipal needs by embracing smart initiatives. Senior-level city managers, consultants, and technologists invoked vocabularies of smartness and innovation, adopting Internet of Things (IoT) and artificial intelligence (AI) as tools to facilitate human resource and service efficiency needs. I found persistent ambiguity in how city managers described and measured outcomes for city smartness. I also found stakeholders used smartness to participate in global knowledge sharing coalitions with public and private entities, amplifying negotiation potential, and producing values of prestige around novel technological innovation. In so doing, public and private stakeholders formed individual and organizational identities around technological innovation, creating invisible tensions between human resource and technology investments, characterized by celebration of innovation work to the detriment of maintenance labors. My findings inform ongoing scholarship by explaining how smart city technologists sold a discourse of innovation that was not entirely compatible with how cities bureaucratically functioned. Such distinction is important to communicate to scholarly audiences unfamiliar with techno-fetishisms, but familiar with urban management critiques. Moreover, my study opens paths to understanding how private interests influence municipal management through more obscured means

When Things Matter: A Data-Centric View of the Internet of Things

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. While IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy, and continuous. This article surveys the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed

Mechatronics & the cloud

Conventionally, the engineering design process has assumed that the design team is able to exercise control over all elements of the design, either directly or indirectly in the case of sub-systems through their specifications. The introduction of Cyber-Physical Systems (CPS) and the Internet of Things (IoT) means that a design team’s ability to have control over all elements of a system is no longer the case, particularly as the actual system configuration may well be being dynamically reconfigured in real-time according to user (and vendor) context and need. Additionally, the integration of the Internet of Things with elements of Big Data means that information becomes a commodity to be autonomously traded by and between systems, again according to context and need, all of which has implications for the privacy of system users. The paper therefore considers the relationship between mechatronics and cloud-basedtechnologies in relation to issues such as the distribution of functionality and user privacy