The IoT is the inter-networking of connected and smart devices, buildings, vehicles and other items which are embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data. A sensor is a detection device that measures, records, or responds to a physical property. Sensors represent the front end of information processing. Progress in communication technologies is part of the multi-factorial advances in electronics, sensors, embedded computing, signal processing and machine learning methods that has led to the development of new capabilities in the IoT. This edited book focuses on the technologies constituting the IoT from a sensor perspective, for an audience of researchers, scientists, engineers and graduate students with an interest in the field. Applications covered include connected sensors for smart cities, energy infrastructure, emergency management, and smart ports.

Sand painting is a form of combination of arts and modern aesthetic, which relies on profound cultural heritage and cultural connotation. To provide the public and artists with an opportunity to better understand sand painting and make art creations surprisingly, this paper proposes a self-adaptive algorithm to simulate sand painting in a real-time way. Our simulation system exploits the height field to simulate sand flow to achieve a fast even real-time target. Seven frequently-used styles of painting techniques are elaborately defined and successfully simulated in our system, including pouring, seeping, dotting, stroking, sweeping, multi-stroking, and pinching. The procedure of sand flow is mainly consist of two key parts: sand accumulation and collapse. The direction field is introduced into the system to control a similar appearance of a normal distribution, which will be of benefit to sand accumulation algorithm. A selfadaptive approach is taken advantage of into sand collapse algorithm to present certain appearances with various details. A color factor is also considered for realistic simulation in this paper in two ways: one is the background color of sand table/canvas and the other is the natural color of sand particles themselves. User feedbacks and experimental results reveal that the algorithm of sand painting simulation in this paper can realize kinds of sand painting arts of creations easily, realistically, effectively and interactively.

Clothing parsing is significant to many clothing applications. Recently, a lot of clothing parsing methods have been presented, which explore the innovation of the parsing pipeline or try to find more specific prior information. Although these methods perform well in some benchmarks, a few challenging problems have not been solved yet, such as the complicated mutual interference among labels. In this study, the authors propose a Conditional Progressive Network to parse clothing in different scales and prevent the mutual interference among labels. The authors’ solution consists of three sub-networks, including Conditional Parsing Network (CPN), Pose Estimation Network (PEN) and Label Transform Network (LTN). Specifically, the CPN module generates the intermediate parsing result in the form of the multiple progressive stages, which combines with the previous outputs in each stage and the specific prior conditions. The PEN module provides a series of heat maps about the human pose information. The LTN module suppresses the redundant labels to avoid the mutual interference among labels. They demonstrate their solution in parsing the fashion clothing cases on the ATR and the Fashion dataset. In their experiments, their method obtains a better performance than the state-of-the-art methods.

The article shows that digital twin technology is not just affecting how buildings are designed and used, it is also impacting on how they are constructed. In the case of the architectural and construction sector, the digital twin arrives as an upgrade on its worthy predecessor, BIM. Building information modelling has been around for over a decade and theoretically stays with a building through its concept, design, construction and operation. The article states that the problem with BIM, is that it is misused both as a term and in its function. Stakeholders still misuse the term and say that it's just a piece of software I need to have on this project. It's a fundamental requirement now of government projects in the UK and that's increasingly the case globally. But it is not one software package, it's an entire process that informs the entire construction.

With autonomous cars closer to reality than concept, Millbrook has made a digital twin of its test track so this new breed of vehicles can be safely put through their paces. Millbrook's digital twin is a simulation environment where autonomous vehicles can experience thousands of hours of accelerated virtual testing while being subjected to varying driving conditions and interacting with other vehicles and pedestrians.

New alternatives for monitoring the ceramic grinding process have been studied. Monitoring vibration signals is one of the most successful methods because some characteristics that describe the behaviour and influence of the process on ground parts are only noticeable by studying such signals. This study aims to monitor the finishing of advanced ceramics during the surface grinding process via digital processing of the vibration signals. Experimental tests were performed using a surface tangential grinding machine with a diamond grinding wheel and alumina (Al₂O₃) test specimens. The vibration signal was measured by an accelerometer and recorded by an oscilloscope at a 2 MHz sampling rate. The tests were conducted at different depths of cut for two workpiece speeds (v _w) under mild and severe machining conditions. Confocal microscopy and surface roughness R_a measurements were performed after grinding each workpiece to classify the samples. Digital signal processing was performed to achieve feature extraction. A frequency range of 800 Hz–2 kHz was most strongly related to the post-grinding ceramic condition. A correlation was found between vibration and integrity of the ceramic workpiece because the vibration signal was proportional to the surface roughness for each cutting depth used. To support the conclusion presented, a statistical analysis through variance by analysis of variance was performed.

Data-driven innovation in sectors such as built environment and transport is gaining traction in research, government and industrial communities. A number of industry-academic collaborations are emphasizing on use of data to empower emerging technologies. Large scale deployments of IoT devices and sensors are making data available at an unprecedented scale. This is leading to design and development of governed data infrastructures to harness the value of socio-technological processes and maximise the economic impact. Application of cognitive technologies such as machine learning and artificial intelligence is paving way for newer ways of data-driven innovation for decision making, predictive analysis and scenario modelling. The paper describes the various building blocks of the data-innovation engine and substantiates it through an anonymised real-world use-case from the built environment. It describes the emerging data-driven innovation models in these sectors and the corresponding value created by them. Finally, it proposes an impact assessment framework to understand and evaluate data-driven innovation in an organisation.

Chatty Factories is a three-year investment by the Engineering and Physical Sciences Research Council (EPSRC) through its programme for New Industrial Systems. The project explores the transformative potential of placing IoT-enabled data driven systems at the core of design and manufacturing processes. The research focuses on the opportunity to collect data from IoT-enabled sensors embedded in products during real-time use by consumers, explores how that data might be immediately transferred into usable information to inform design, and considers what characteristics of the manufacturing environment might optimise the response to such data. The project also considers implications arising for skills development in the education sector as well as ethics in manufacturing. In this paper we provide a vision for future “Chatty Factories”.

Personal data is an essential component of business models using the Internet of Things (IoT). Massive volumes of personal data are being recorded and analysed about consumers, despite them having limited understanding about how it affects them. Perceptions and preferences in this space influence how consumers choose to interact with the IoT, to a large extent. Yet little is understood about how industry perceives the views of consumers regarding the use of their personal data. To address this gap, we conducted three workshops with IoT industry stakeholders exploring their perspectives of consumer conceptions of the value of personal data in IoT. From the workshops, three overarching analytical themes emerged: (1) A perception of a significant gap between industry and consumers' understanding of what personal data is, who owns it, how it is used in IoT products and how it drives value in IoT businesses; (2) Perceived imbalances of power between industry and consumers in the control of and value extracted from personal data, with implications for inequalities between different consumer groups; and (3) A need for greater education and transparency for consumers, and for industry, about how personal data can be used. We develop a tentative five-point manifesto for the use of personal data in IoT, and conclude that a deeper understanding of consumer perspectives by industry would be positive for the ethical development of the IoT.

Transport network infrastructure including the use of Intelligent Transport Systems (ITS) is fundamental to the mobility of people and shipments. This study aims at understanding how different ITS measures may impact multiple traffic engineering goals with respect to a set of Key Performance Indicators (KPIs). The ordering of KPIs is determined by the preferences of the decision maker. A Multi-Criteria Decision Analysis framework is proposed for impact assessments of ITS measures. Data about KPIs is derived with the help of traffic data gathered from the Gothenburg Region. Comparing the contributions of ITS measures to different goals suggest that the management of flow and speed in a road network is crucial for improving capacity utilisation. The goal assessments are then projected onto different use-cases in terms of socio-economic impacts. The result indicates that corridor section traffic management, transport management (focusing on transit traffic) and urban gate-way will generate socio-economic effects, respectively, in a decreasing order. Urban gateway is particularly interesting because it is the least intrusive and less costly use-case.