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With the demand for accurately recognizing human actions and environmental situations, multifunctional sensors are essential elements for smart applications in various emerging technologies, such as smart robots, human-machine interface, and wearable electronics. Low-dimensional materials provide fertile soil for multifunction-integrated devices. This review focuses on the multifunctional sensors for mechanical stimulus and environmental information, such as strain, pressure, light, temperature, and gas, which are fabricated from low-dimensional materials. The material characteristics, device architecture, transmission mechanisms, and sensing functions are comprehensively and systematically introduced. Besides multiple sensing functions, the integrated potential ability of supplying energy and expressing and storing information are also demonstrated. Some new process technologies and emerging research areas are highlighted. It is presented that optimization of device structures, appropriate material selection for synergy effect, and application of piezotronics and piezo-phototronics are effective approaches for constructing and improving the performance of multifunctional sensors. Finally, the current challenges and direction of future development are proposed.

By now, there have been many standards battles fought within the same industry or by multiple industries in the market-based standardization. In these battles, incompatible standards compete to win market dominance. While there is some research on standards battles found within a single committee, competitions in the committee-based standardization between standards from different committees or SDOs are underexplored. This paper categorizes the types of standards battles by the mode of standardization and the heterogeneity of actors. A new type referred to as ‘committee standards battles for converging systems’ is introduced and the dynamics of such battles is explored with two cases. The battle between the electric vehicle charging and the smart meter communication standard and the battle between two different vehicle-to-everything (V2X) communication standards are analyzed. The failure in achieving compatibility between different committee standards on the same frequency bands results in communication interference that adversely affects the operation of smart systems. Social incompatibilities between actors and alliances from a mix of industries with vested interests towards a particular standard complicate the battling scene. The findings provide implications in terms of heterogeneity, actors, and government role in standards battles.

Blockchain technologies have recently come to the forefront of the research and industrial communities as they bring potential benefits for many industries. This is due to their practical capabilities in solving many issues currently inhibiting further advances in various industrial domains. Securely recording and sharing transactional data, establishing automated and efficient supply chain processes, and enhancing transparency across the whole value chain are some examples of these issues. Blockchain offers an effective way to tackle these issues using distributed, shared, secure, and permissioned transactional ledgers. The employment of blockchain technologies and the possibility of applying them in different situations enables many industrial applications through increased efficiency and security; enhanced traceability and transparency; and reduced costs. In this paper, different industrial application domains where the use of blockchain technologies has been proposed are reviewed. This paper explores the opportunities, benefits, and challenges of incorporating blockchain in different industrial applications. Furthermore, the paper attempts to identify the requirements that support the implementation of blockchain for different industrial applications. The review reveals that several opportunities are available for utilizing blockchain in various industrial sectors; however, there are still some challenges to be addressed to achieve better utilization of this technology.

The interactions between humans and unmanned aerial vehicles (UAVs), whose applications are increasing in the civilian field rather than for military purposes, are a popular future research area. Human–UAV interactions are a challenging problem because UAVs move in a three-dimensional space. In this paper, we present an intelligent human–UAV interaction approach in real time based on machine learning using wearable gloves. The proposed approach offers scientific contributions such as a multi-mode command structure, machine-learning-based recognition, task scheduling algorithms, real-time usage, robust and effective use, and high accuracy rates. For this purpose, two wearable smart gloves working in real time were designed. The signal data obtained from the gloves were processed with machine-learning-based methods and classified multi-mode commands were included in the human–UAV interaction process via the interface according to the task scheduling algorithm to facilitate sequential and fast operation. The performance of the proposed approach was verified on a data set created using 25 different hand gestures from 20 different people. In a test using the proposed approach on 49,000 datapoints, process time performance of a few milliseconds was achieved with approximately 98 percent accuracy.

Modern control strategies for district-level heating and cooling supply systems pose a difficult challenge. In order to integrate a wide range of hot and cold sources, these new systems will rely heavily on accumulation and much lower operating temperatures. This means that predictive models advising the control strategy must take into account long-lasting thermal effects but must not be computationally too expensive, because the control would not be possible in practice. This paper presents a simple but powerful systematic approach to reducing the complexity of individual components of such models. It makes it possible to combine human engineering intuition with machine learning and arrive at comprehensive and accurate models. As an example, a simple steady-state heat loss of buried pipes is extended with dynamics observed in a much more complex model. The results show that the process converges quickly toward reasonable solutions. The new auto-generated model performs 5 &times, 104 times faster than its complex equivalent while preserving essentially the same accuracy. This approach has great potential to enhance the development of fast predictive models not just for district heating. Only open-source software was used, while OpenModelica, Python, and FEniCS were predominantly used.

Distributed systems provide smart functionality to everyday objects with the help of wireless sensors using the internet. Since the last decade, the industry is struggling to develop efficient and intelligent protocols to integrate a huge number of smart objects in distributed computing environments. However, the main challenge for smart and distributed system designers lies in the integration of a large number of heterogeneous components for faster, cheaper, and more efficient functionalities. To deal with this issue, practitioners are using edge computing along with server and desktop technology for the development of smart applications by using Service-Oriented Architecture (SOA) where every smart object offers its functionality as a service, enabling other objects to interact with them dynamically. In order to make such a system, researchers have considered context-awareness and Quality of Service (QoS) attributes of device services. However, context modeling is a complicated task since it could include everything around the applications. Moreover, it is also important to consider non-functional interactions that may have an impact on the behavior of the complete system. In this regard, various research dimensions are explored. However, rich context-aware modeling, QoS, user priorities, grouping, and value type direction along with uncertainty are not considered properly while modeling of incomplete or partial domain knowledge during ontology engineering, resulting in low accuracy of results. In this paper, we present a semantic and logic-based formal framework (hybrid) to find the best service among many candidate services by considering the limitations of existing frameworks. Experimental results of the proposed framework show the improvement of the discovered results.

Since the 1990's, researchers in both academia and industry have been exploring ways to exploit the potential for Wireless Sensor Networks (WSNs) to revolutionize our understanding of - and interaction with - the world around us. WSNs have therefore been a major focus of research over the past 20 years. While WSNs offer a persuasive solution for accurate real-time sensing of the physical world, they are yet to be as ubiquitous as originally predicted when the technology was first envisaged. Technical difficulties exist which have inhibited the anticipated uptake in WSN technologies. The most challenging of these have been identified as system reliability, battery lifetime, maintenance requirements, node size and ease of use. Over the past decade, the Wireless Sensor Networks (WSN) group at the Tyndall National Institute, has been at the forefront of driving the vision of ubiquitously deployed, extended lifetime, low power consumption embedded systems providing information rich data streams wirelessly in (close to) real-time. In this time, the WSN group has developed multiple novel, first of kind, wireless multi-sensor systems and deployed these in the world around us, overcoming the technical challenges associated with ensuring robust and reliable long-term data sets from our environment. This work is focused on investigating and addressing these challenges through the development of the new technologies and system integration methodologies required to facilitate and implement WSNs and validate these in real deployments. Specifically, discussed are the development and deployment of novel WSN systems in the built environment, environmental monitoring and fitness and health monitoring systems.The key research challenges identified and discussed are:a)The development of resource-constrained, extremely low power consumption systems incorporating energy-efficient hardware and software algorithms.b)The development of highly reliable extremely long duration deployments which through the use of appropriate energy harvesting solutions facilitate (near) zero maintenance sensor networks.c)The development of low power consumption miniaturized wearable microsysteThe development of technologies to address these challenges in terms of cost, size, power consumption and reliability which need to be tested and validated in real world deployments of wireless sensing systems is discussed. It is clear that when looking at the scale up of deployments of novel WSNs, that to be successful, such systems need to "be invisible, last forever, cost nothing and work out of the box". This paper describes these relevant technologies and associated project demonstrators

The cyber processing layer of smart systems based on a cognitive dynamic system (CDS) can be a good solution for better decision making and situation understanding in non-Gaussian and nonlinear environments (NGNLE). The NGNLE situation understanding means deciding between certain known situations in NGNLE to understand the current state condition. Here, we report on a cognitive decision-making (CDM) system inspired by the human brain decision-making. The simple low-complexity algorithmic design of the proposed CDM system can make it suitable for real-time applications. A case study of the implementation of the CDS on a long-haul fiber-optic orthogonal frequency division multiplexing (OFDM) link was performed. An improvement in Q-factor of ~7 dB and an enhancement in data rate efficiency ~43% were achieved using the proposed algorithms. Furthermore, an extra 20% data rate enhancement was obtained by guaranteeing to keep the CDM error automatically under the system threshold. The proposed system can be extended as a general software-based platform for brain-inspired decision making in smart systems in the presence of nonlinearity and non-Gaussian characteristics. Therefore, it can easily upgrade the conventional systems to a smart one for autonomic CDM applications.

The subject of research is the activities of state institutions aimed at the development of digital technologies in the economy and other spheres of society life, particularly intelligent technologies for decision support and making. The purpose of research was to determine the prospects for using intelligent technologies in the federal risk management system. In the context of the Quality of Life problem solution, an approach to creating a factor model of the problem domain of ensuring security and sustainable socio-economic development is shown. The model identifies 12 spheres combining 72 interrelated factors. Problems and threats to be solved and overcome in the process of development and wide promotion of intelligent information technologies in the practice of managing socio-economic systems are considered. It is concluded that intelligent systems used for managing socio-economic systems must undergo strict verification of not only their adequacy but also to expose possible user manipulation devices embedded in them.

In today’s technology, when costs of time, energy and human resources are considered, efficient use of resources provides significant advantages over many aspects. In light of this, role of building automation systems, which are a part of smart cities, become even more important. At the very core of building automation systems there lies the efficient use of resources and systems for providing comfortable living situations. With the advancement in network technology, systems can be programmed smartly and any malfunctions on the systems can be detected and fixed remotely. In addition to that, all data gathered during this process can be analyzed to create machine learning solutions for a system to control and program itself. In this work, we pulled the sensor data and developed an interface to do analysis. Our aim is to understand how the system behaves. This interface will be the basis of our work on developing machine learning algorithms to predict system behaviour for programming the system for energy.

Analog components are fundamental blocks of smart systems, as they allow a tight interaction with the environment, in terms of both sensing/actuation and communication. This impacts on the design of the overall system, and mainly on the validation phase, that thus requires the joint simulation of digital and analog aspects. In this scenario, this paper proposes the automatic conversion of analog models to C++-based languages, to remove the overhead of co-simulation with traditional virtual platform tools. The proposed methodology allows to convert a given analog description to either: 1) a fully equivalent description or 2) an abstract representation for faster simulation which models only the aspects of interest. Effectiveness and correctness have been proved on a number of case studies that highlight the effectiveness and potentiality of the proposed methodology.

The design, manufacturing, and preliminary testing of a smart patch sensor named MonitoRing are herein presented. The sensor is conceived to identify amplitude and direction of structural loads by distributed strain profile detection along its circular geometry. The sensor is manufactured by using flexible glass/epoxy laminates hosting a single standard telecom fiber optic. The fiber optic is embedded according to three loops, different by radius and quote. The sensor is then externally bonded on a structural element and able to follow the deformations under tensile and bending loading condition. The optical Rayleigh backscattering technology provides an interrogation of strain with high spatial resolution all along the fiber path. The load and direction identification is hence, provided by comparing amplitude, phase and sign of deformation spectrum of each loop. Preliminary numerical and experimental result, are reported and analyzed for simple test cases.

Energy consumption is steadily increasing in the Kingdom of Saudi Arabia (KSA), which imposes continuous strains on the electrical load. Furthermore, consumption rationalization measures do not seem to improve the situation in any way. Therefore, the implementation of energy saving policies become an urgent need. This paper targets developing a smart energy-saving framework for integrating new advanced technologies and conventional Air Conditioning (AC) systems to achieve a comfortable environment, optimum energy efficiency and profitability. In this paper, a three-stage smart control framework, which allows controlling room temperature according to the user&rsquo, s preferences, is implemented. The first stage is a user identification process. In the second stage, a Petri Nets (PN) model monitors users and sends their preferred temperatures to the third stage. A PID controller is implemented in the third stage to regulate room temperatures. The interconnected sensing and actuating devices in this smart environment are configured to provide users with comfort and energy saving functionality. Experimental results show the good performances and features of the proposed approach. The proposed smart framework reduces the energy consumption of the current ON/OFF controller ( 219 . 09 kW) by a significant amount which reaches ( 116 . 58 kW) by ratio about 46 . 79 % . Reducing energy consumption is one of these important features in addition to system reactivity and user comfort.

The structural engineering community has a strong responsibility to contribute to a more efficient use of natural resources. Nowadays the construction industry is by far the most resource intense industry sector, approximately 40-50% of all primary raw materials are used, which raises the question about the architects and engineer’s accountability. In this context and as a result of the Paris Climate agreement the Dutch government defined the program “Nederland Circulair in 2050”, which states the ambition to use 50% less primary materials in 2030 and to have a full circular economy in 2050.One possible approach to achieve these ambitious goals is the application of renewable, bio-based materials in the built environment and to replace traditional, typically cement-based, materials. Already in the past natural building materials, such as timber and bamboo have been used widely, but in recent years new materials came up and provide new opportunities to be used in the construction industry. The authors explored various alternatives, such as hemp and flax fibres, mycelium and lignin-based fibres for composite materials, which will be described with various experimental and realised case studies.

International audience; Industrial monitoring environments have evolved from single monolithic systems to widely distributed heterogeneous systems. These include the Internet of Things (IoT), Industrial IoT, Cyber-Physical Systems, and Enterprise Application. One of the key challenges is the integration of heterogeneous systems and data exchange interoperability. In the industrial smart gas project, in which this work takes place, current standard-based or middleware solutions are not sufficient to handle these issues and often require specific ad hoc developments. This paper proposes a generic, modular, and extensible interoperability architecture based on modeling principles. We provide a free software implementation and illustrate the approach on industrial use cases. Some criteria are then proposed for a first qualitative evaluation.

Prolonged seated works are responsible of awkward poses (e.g., excessive neck forward flexion) and job stressful conditions. Musculoskeletal disorders in the cervical spine region are common in computer workers who are often affected by neck pain. Neck pain has a high prevalence amongst the general population (from 42% to 69%). Reduction of workers productivity, absence from work and utilization of health care services worsen the socioeconomic burden associated to neck pain. Early evaluation of postural mistakes and changes in vital signs associated to job stress may be beneficial to reduce the incidence of neck pain. To reach this aim, wearable systems based on different sensing technologies have been developed. In the last decades, smart systems based on fiber Bragg grating sensors (FBGs) have been extensively used for instrumenting wearables. The present work aimed at preliminary assessing the capability of an FBG-based smart system in detecting single-plane neck movements associated to poor postural habits and respiratory frequency changes associated to stressful working conditions. Results confirmed the system capability in detecting flexion/extension movements in the sagittal plane and its good accuracy in monitoring respiratory frequency during computer work.

We live in complex times in the health, social, political, and energy spheres, and we must be aware of and implement new trends in intelligent social health systems powered by the Internet of Things (IoT). Sustainable development, energy efficiency, and public health are interrelated parameters that can transform a system or an environment for the benefit of people and the planet. The integration of sensors and smart devices should promote energy efficiency and ensure that sustainable development goals are met. This work is carried out according to a mixed approach, with a literature review and an analysis of the impact of the Sustainable Development Goals on the applications of the Internet of Things and smart systems. In the analysis of results, the following questions are answered about these systems and applications: (a) Are IoT applications key to the improvement of people’s health and the environment? (b) Are there research and case studies implemented in cities or territories that demonstrate the effectiveness of IoT applications and their benefits to public health? (c) What sustainable development indicators and objectives can be assessed in the applications and projects analyzed?

A linear programming framework is proposed to model distribution network characteristics, and market clearing processes for flexible load and distributed energy resources providing reserve and reactive power compensation. One shows that the Nash equilibrium solution representing the interaction between utility and customers for demand response and distributed reserve transactions can be approximated by a linear program when the players (i.e. the customers) are numerous and tend to become infinitesimal. Then a linear program is shown to reveal the market prices, corresponding to the marginal cost for the utility. The goal in developing this model is to provide a new module for a regional long term model of development of smart energy systems. This module will then introduce in the modeling of energy transition, the new options and constraints that are provided by a penetration of renewables with the possibility of implementing distributed markets for demand response and system services permitted by the development of the cyber-physical layer. A case study of a potential smart urban distribution network in Europe is carried out and provides numerical results that illustrate the proposed framework.

Editorial du Numéro spécial : Emerging ICT concepts for smart, safe and sustainable industrial systems; International audience; This editorial introduces the special issue on Emerging Information and Communication Technology (ICT) concepts for smart, safe and sustainable industrial systems in the Elsevier journal Computers in Industry. The 13 papers in this special issue were selected because of their high quality and also because they propose emerging ICT solutions that address at least one of the three dimensions we suggest are basic requirements to design usable future Industrial Systems that must be safe, smart and sustainable. Previous global discussions about the state of the art with regard to the topic of this special issue are provided, as well as exploratory guidelines for future research in this area.

Today’s best-effort (BE) Internet of Things (IoT) faces challenges in providing the end-to-end-performance, security, and energy efficiency needed for the Smart Systems of the 21st century. These future smart systems will include smart cities , smart transportation systems , and smart manufacturing . This paper surveys the security weaknesses of the BE IoT. The BE-IoT cannot be partitioned into distinct interference-free virtual networks , which compromises performance, cyber-security, and energy efficiency. The design of a secure deterministic industrial-tactile IoT core network, which can embed millions of distinct secure deterministic virtual networks (SD-VNs) in layer 2, is then presented. Deterministic communications, combined with low-jitter scheduling, offers several benefits: 1) the removal of all congestion, interference, and DOS attacks; 2) a significant reduction in IoT router buffer sizes; 3) a significant reduction in IoT energy use; 4) a reduction of end-to-end IoT delays to the speed of light in fiber; and 5) deterministic packet-switches are relatively easy to synthesize using FPGA technologies. These benefits apply to optical and 5G wireless networks. Future smart systems can reserve their own congestion-free SD-VNs in layer 2 to manage their traffic, with significantly improved performance, security, and energy efficiency. A speed-of-light deterministic IoT core network can transform cloud services in the 21st century by exploiting a new technology: FPGAs combined with silicon photonics transceivers to achieve terabits/second of optical bandwidth. To illustrate the transformational potential, Big Data green cloud computing over a secure deterministic IoT spanning the European Union is explored.

Biomolecular machines are widely present in nature, especially in complex living organisms, and are involved in important biological processes. Inspired by nature and increasingly mature synthetic technologies, a series of artificial molecular machines (AMMs) that exhibit similar processes and functions as biomolecular counterparts have been developed, and to date, some dramatic achievements have been obtained. Herein, the use of AMMs in smart systems and materials with controllable regulations and interesting functions are summarized, presenting the specific micro‐ to macroscale applications in solid surface modification, transmembrane transport, smart catalysts, liquid crystals, artificial molecular muscles, and stimuli‐responsive polymers. The challenges of developing novel complex AMMs with intelligent functions are discussed, and some potential solutions are proposed.

E-commerce is becoming more and more the main instrument for selling goods to the mass market. This led to a growing interest in algorithms and techniques able to predict products future prices, since they allow us to define smart systems able to improve the quality of life by suggesting more affordable goods and services. The joint use of time series, reputation and sentiment analysis clearly represents one important approach to this research issue. In this paper we present Price Probe, a suite of software tools developed to perform forecasting on products&rsquo, prices. Its primary aim is to predict the future price trend of products generating a customized forecast through the exploitation of autoregressive integrated moving average (ARIMA) model. We experimented the effectiveness of the proposed approach on one of the biggest E-commerce infrastructure in the world: Amazon. We used specific APIs and dedicated crawlers to extract and collect information about products and their related prices over time and, moreover, we extracted information from social media and Google Trends that we used as exogenous features for the ARIMA model. We fine-estimated ARIMA&rsquo, s parameters and tried the different combinations of the exogenous features and noticed through experimental analysis that the presence of Google Trends information significantly improved the predictions.

International audience; Smart and sensing systems represent a significant research theme that has motivated a number of research initiatives around the world. Smart systems typically consist of different components including sensors for signal acquisition, communication units for data transmission between components, control and management units for decision-making, and actuators to perform the appropriate actions. They have impacted applications in many fields such as manufacturing, healthcare, energy, environment, logistic, defence, monitoring, and mobility. As the complexity of such systems continue to grow, the challenge of developing integrated smart and sensing systems has surpassed the design complexity of their individual components. A smart and sensing system may include a large number of heterogeneous components, subsystems, smart and intelligent sensors, and may combine several correlated functionalities. Thus, the main issue of developing smart and sensing systems lies in the complexity to integrate and to manage these different components, technologies, and goals across a wide spectrum. In recent years, the emergence of IoT has amplified the capacity of sensing the world through a network of connected devices using the existing network infrastructure. Grouping together smart and sensing systems in an IoT setting to form large-scale distributed cyber-physical systems has tremendous potential in bringing smart systems to many application domains.This Journal’s Special Issue (SI) aims to promote relevant researches related to strategic views, problems, trends, solutions, and applications of IoT for Smart and Sensing Systems. This represents a more specialized area of interest than the wide application of IoT. The issue focuses more specifically on how industrial IoT contributes to the development of smart and sensing systems.

With the evolution of the Internet of things and smart cities, a new trend of the Internet of simulation has emerged to utilise the technologies of cloud, edge, fog computing, and high-performance computing for design and analysis of complex cyber-physical systems using simulation. These technologies although being applied to the domains of big data and deep learning are not adequate to cope with the scale and complexity of emerging connected, smart, and autonomous systems. This study explores the existing state-of-the-art in automating, augmenting, and integrating systems across the domains of smart cities, autonomous vehicles, energy efficiency, smart manufacturing in Industry 4.0, and healthcare. This is expanded to look at existing computational infrastructure and how it can be used to support these applications. A detailed review is presented of advances in approaches providing and supporting intelligence as a service. Finally, some of the remaining challenges due to the explosion of data streams; issues of safety and security; and others related to big data, a model of reality, augmentation of systems, and computation are examined.

To provide sufficient food and fiber to the increasing global population, the technologies associated with crop protection are growing ever more sophisticated but, at the same time, societal expectations for the safe use of crop protection chemistry tools are also increasing. The goal of this perspective is to highlight the key issues that face future leaders in crop protection, based on presentations made during a symposium titled "Developing Global Leaders for Research, Regulation and Stewardship of Crop Protection Chemistry in the 21st Century", held in conjunction with the IUPAC 13th International Congress of Pesticide Chemistry in San Francisco, CA, USA, during August 2014. The presentations highlighted the fact that leaders in crop protection must have a good basic scientific training and understand new and evolving technologies, are aware of the needs of both developed and developing countries, and have good communication skills. Concern is expressed over the apparent lack of resources to meet these needs, and ideas are put forward to remedy these deficiencies.

International audience; Micro Electro-Mechanical Systems (MEMS), applied to the field of hearing aids, offer ample possibilities for improving of performance, reliability and functional specifications, and they are also promising in terms of energy saving. In this paper, some of the major design problems relating to the use of MEMS for sound waves generation inside the ear canal are analyzed.

Smart systems are characterised by their ability to analyse measured data in live and to react to changes according to expert rules. Therefore, such systems exploit appropriate data models together with actions, triggered by domain-related conditions. The challenge at hand is that smart systems usually need to process thousands of updates to detect which rules need to be triggered, often even on restricted hardware like a Raspberry Pi. Despite various approaches have been investigated to efficiently check conditions on data models, they either assume to fit into main memory or rely on high latency persistence storage systems that severely damage the reactivity of smart systems. To tackle this challenge, we propose a novel composition process, which weaves executable rules into a data model with lazy loading abilities. We quantitatively show, on a smart building case study, that our approach can handle, at low latency, big sets of rules on top of large-scale data models on restricted hardware., Comment: pre-print version, published in the proceedings of MOMO-17 Workshop

Modern smart systems are usually built by implementing SW functionalities executed on HW platforms composed of both digital and analog components. Validation is mainly implemented through simulation of the functional behavior of the entire smart system modeled by a Virtual Platform. It is thus crucial to achieve fast mixed-signal simulation by removing unnecessary overhead due to synchronization between multiple tools and unimportant details. This work proposes a methodology to abstract mixed-signal systems, by integrating digital and analog components in a homogeneous virtual platform model for efficient simulation. Two main contributions are provided: 1) an automatic abstraction technique for analog components, allowing to preserve only the details meaningful for the functional behavior of the entire platform by moving complexity from simulation to generation time and 2) a novel scheduling technique that exploits temporal decoupling and synchronization of digital and analog processes, to simulate them together in a homogeneous model.

Part 3: Systems Analysis; International audience; The Internet-of-Things (IoT) is today a reality, and Smart Systems have taken advantage of this to improve its own sense, act and control capabilities. IoT is a highly heterogeneous environment composed by a vast number of “things” (sensors, smart objects, etc.). These “things” are based on hardware platforms which can differ widely since manufactures are being capable of develop new devices every day to tackle different application domains. Consequently, a problem emerges regarding which will be the suitable, proper hardware solution for an IoT deployment. Make a right decision is probably one of the toughest challenges for science and technology managers. This work proposes a novel methodology to analyze a set of hardware alternatives based on user’s multi-criteria requirements, and advice on the more suitable hardware solution for a specific situation. For proof-of-concept it is used different Arduino boards as hardware alternatives, in which user requirements are based on hardware features. This methodology foresees its use during the development of Smart Systems (e.g.: Transportation, Healthcare) to optimize the selection of hardware platforms.

Layer-by-Layer (LbL) assembly is a simple and highly versatile method tomodify surfaces and fabricate robust and highly-ordered nanostructured coatingsover almost any type of substrate. Such versatility enables the incorporationof a plethora of building blocks, including materials exhibiting switchableproperties, in a single device through a multitude of complementary intermolecularinteractions. Switchable materials may undergo reversible physicochemicalchanges in response to a variety of external triggers. Althoughmost of the works in the literature have been focusing on stimuli-responsivematerials that are sensitive to common triggers such as pH, ionic strength, ortemperature, much less has been discussed on LbL systems which are sensitiveto non-invasive and easily controlled light stimulus, despite its uniquepotential. This review provides a deep overview of the recent progressesachieved in the design and fabrication of light-responsive LbL polymericmultilayer systems, their potential future challenges and opportunities, andpossible applications. Many examples are given on light-responsive polymericmultilayer assemblies built from metal nanoparticles, functional dyes, and metal oxides. Such stimuli-responsive functional materials, and combinationsamong them, may lead to novel and highly promising nanostructured smartfunctional systems well-suited for a wide range of research fields, includingbiomedicine and biotechnology., The research leading to this work has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no REGPOT-CT2012-316331-POLARIS, and from QREN (ON.2 - NORTE-01-0124-FEDER-000016). The research was also funded by FEDER through the Competitive Factors Operational Program (COMPETE) and by National funds through the Portuguese Foundation for Science and Technology (FCT) in the scope of the projects PTDC/FIS/115048/2009 and PTDC/CTM-BIO/1814/2012. J. Borges and L. C. Rodrigues contributed equally to this work.

The described application directs the integration of capacitive and resistive sensors for environmental parameters monitoring (CO2, relative humidity, dew point and temperature) in low cost applications which can be made on flexible substrate, which was developed in the European FP7 project INTERFLEX [1]. This type of applications on plastic substrates requires a reduction of amount and type of components in order to reduce costs through simplification of assembly processes as well as enhancement of the reliability.This paper describes a very simple low power and cost effective architecture for readout of capacitive and resistive sensors, which uses few external components, exploiting a STMicroelectronics STM8L15x microcontroller and sensors developed by Fraunhofer Research Institution for Modular Solid State Technologies (EMFT).

In this review, we discuss the role of sensor analytics point solutions (SNAPS), a reduced complexity machine-assisted decision support tool. We summarize the approaches used for mobile phone-based chemical/biological sensors, including general hardware and software requirements for signal transduction and acquisition. We introduce SNAPS, part of a platform approach to converge sensor data and analytics. The platform is designed to consist of a portfolio of modular tools which may lend itself to dynamic composability by enabling context-specific selection of relevant units, resulting in case-based working modules. SNAPS is an element of this platform where data analytics, statistical characterization and algorithms may be delivered to the data either via embedded systems in devices, or sourced, in near real-time, from mist, fog or cloud computing resources. Convergence of the physical systems with the cyber components paves the path for SNAPS to progress to higher levels of artificial reasoning tools (ART) and emerge as data-informed decision support, as a service for general societal needs. Proof of concept examples of SNAPS are demonstrated both for quantitative data and qualitative data, each operated using a mobile device (smartphone or tablet) for data acquisition and analytics. We discuss the challenges and opportunities for SNAPS, centered around the value to users/stakeholders and the key performance indicators users may find helpful, for these types of machine-assisted tools.

Intelligent tire concept constitutes one of the approaches to increase the accuracy of active safety systems in vehicle technology. The possibility of detecting tire&ndash, road interactions instantaneously has made these systems one of the most important research areas in automotive engineering. This study introduces the use of cost-effective flex and polyvinylidene fluoride strain sensors to estimate some dynamic tire features in free-rolling and real working conditions. The proposed solution combines a microcontroller-based readout circuit for the two sensors with a wireless data transmission system. A suitable prototype was realized and first experimental tests were conducted, in the laboratory as well as on the road. The energy consumption of the wireless monitoring system was optimized. Simulated and experimental results validate the proposed solution.

This paper aims to explain the design and implementation procedure of embedded Smart Systems. The idea is supported by four different Smart Systems as Smart Home Smart Agriculture Smart Campus and Seat and Study Module of Smart Library. All designs and implementations contains technological components of embedded systems mobile application development cloud based services and client side graphical user interface. Ultimately this paper gives an overview of current state of the art concerning Smart System Design and discusses several issues and possibilities concerning the implementation of four different systems. © 2016 IEEE.

International audience; Distributed systems spread widely in industrial environments. One of the key challenges is the exchange and the aggregation of data between these sys-tems. Although standards play an important role to solve data interoperability is-sues between systems, these standards do not completely address existing indus-trial problems. In fact, it is not granted to have an industrial environment that complies with a unique standard; therefore, ad-hoc solutions are used to solve this issue. In this article, the authors propose a generic architecture to address the in-teroperability between systems. This architecture is developed based on model-based techniques and principles. Besides, it reduces the need for human interven-tion and time by developing once and reusing the building blocks of the architec-ture. Finally, the architecture is described in its application to a case study.

Smartness in contemporary society implies the use of massive data to improve the experience of people with connected services and products. The use of big data to collect information about people’s behaviours opens a new concept of “user-centred design” where users are remotely monitored, observed and profiled. In this paradigm, users are considered as sources of information and their participation in the design process is limited to a role of data generators. There is a need to identify methodologies that actively involve people and communities at the core of ecosystems of interconnected products and services. Our contribution to designing for social innovation in ecosystems relies on developing new methods and approaches to transform data-driven design using a participatory and co-creative data-enabled design approach. To this end, we present one of the methods we have developed to design “smart” systems called Experiential Design Landscapes (EDL), and two sample projects, Social Stairs and [Y]our Perspective. Social Stairs faces the topic of behaviour change mediated by sensing technologies. [Y]our Perspective is a social platform to sustain processes of deliberative democracy. Both projects exemplify our approach to data-enabled design as a social proactive participatory design approach.

Smart systems are miniaturized devices integrating computation, communication, sensing and actuation. As such, their design can not focus solely on functional behavior, but it must rather take into account different extra-functional concerns, such as power consumption or reliability. Any smart system can thus be modeled through a number of views, each focusing on a specific concern. Such views may exchange information, and they must thus be simulated simultaneously to reproduce mutual influence of the corresponding concerns. This paper shows how the IP-XACT standard, with some necessary extensions, can effectively support this simultaneous simulation. The extended IP-XACT descriptions allow to model extra-functional properties with a homogeneous format, defined by analysing requirements and characteristic of three main concerns, i.e., power, temperature and reliability. The IP-XACT descriptions are then used to automatically generate a skeleton of the simulation infrastructure in SystemC. The skeleton can be easily populated with models available in the literature, thus reaching simultaneous simulation of multiple concerns.

In 2011, the Departments of Architecture, Physics and Engineering began the development of a small Passivhaus standard, renewable energy self-sufficient studio at the University Botanical Gardens in Dundee. The prototype was conceived as an experimental, integrated technical platform to monitor the performance of an ultra-low-energy consumption, energy positive building in the Scottish climate, and understand user behaviour in relation to managing energy in-use and reducing occupant’s energy consumption. The building fabric has been constructed using regional sustainable materials, including a low-thermal bridging timber kit relying on Scottish small cross-section timber and a novel foam concrete (air entrained) slab foundation. While further work is required to complete the installation of the renewable energy system, predictive modelling indicates that energy autonomy can be largely achieved. With the recent introduction of the new Passivhaus 2009 criteria in October 2015, this project provides an insight into the practical application of an autarkic energy system in a northern European climate. The following paper describes the research rationale, the processes and decision making in the development of the formal and technical design of the building and discusses our current thinking in the design and quantification of the energy system.

The paper presents a methodology for the automatic abstraction of analog magnetic components to achieve efficient simulation of complex smart system virtual platform. We aim at facilitating the validation process by allowing the simulation of both functional and extra-functional behaviors of the system with an unified simulation environment. The approach employs a process of simplification which removes unnecessary details of the analog model, enabling a much faster simulation.

In the past, human–machine interfacing (HMI) motivated many studies to develop systems and devices that were able to transfer analog commands from the user's body to machines. However, many design solutions are still affected by comfort and performance limitations due to wire communications, long calibration procedures, resistance to hand motions, and power supplies requiring cables or batteries. GoldFinger, the HMI glove introduced in this paper, has the potential to overcome some of these limitations thanks to the integration of advanced materials, miniaturization of components and electronics, and power generation through biomechanical energy harvesting. Hand motions are used to communicate with the machine via a LED tracking system. Then, information is digitalized with dedicated software that also provides the machine microcontroller programming in the C language. Additionally, the battery discharge time is reduced due to the power harvested from integrated piezoelectric transducers, which generate power from finger motions.

Smart systems represent a broad class of systems defined as intelligent, miniaturized devices incorporating functionality like sensing, actuation, and control. In order to support these functions, they must include sophisticated and heterogeneous components and subsystems such as: application-specific sensors and actuators, multiple power sources and storage devices, intelligence in the form of power management, baseband computation, digital signal processing, power actuators, and subsystems for various types of wireless connectivity (as shown in Fig. 3.1).

This chapter presents two case studies showing how the proposed approach applies to smart system design and optimization. The former is the virtual prototyping platform built for a laser pico-projector actuator, where MEMS, analog and digital components are simulated with the aim of optimizing the resulting image quality by means of firmware tuning. The latter, in the context of wearable equipment for inertial body motion reconstruction, deals with the modeling of an inertial sensor node, supporting system accuracy evaluation and sensor fusion enhancement. Finally, the Open-Source Test Case (OSTC) is described, showing a complete modeling and simulation flow on a publicly available design.

This book-presents new methods and tools for the integration and simulation of smart devices. The design approach described in this book explicitly accounts for integration of Smart Systems components and subsystems as a specific constraint. It includes methodologies and EDA tools to enable multi-disciplinary and multi-scale modeling and design, simulation of multi-domain systems, subsystems and components at all levels of abstraction, system integration and exploration for optimization of functional and non-functional metrics. By covering theoretical and practical aspects of smart device design, this book targets people who are working and studying on hardware/software modelling, component integration and simulation under different positions (system integrators, designers, developers, researchers, teachers, students etc.). In particular, it is a good introduction to people who have interest in managing heterogeneous components in an efficient and effective way on different domains and different abstraction levels. People active in smart device development can understand both the current status of practice and future research directions. Provides a comprehensive overview of smart systems design, focusing on design challenges and cutting-edge solutions; Enables development of a co-simulation and co-design environment that accounts for the peculiarities of the basic subsystems and components to be integrated; Describes development of modeling and design techniques, methods and tools that enable multi-domain simulation and optimization at various levels of abstraction and across different technological domains.

The UK food industry faces significant challenges to remain sustainable. With major challenges, such as Brexit, on the horizon, companies can no longer rely on a low labour cost workforce to maintain low production costs and achieve economic sustainability. Smart Systems (SS) is being seen as an approach towards achieving significant improvements in both economic and environmental sustainability. However, there is little evidence to indicate whether UK food companies are prepared for the implementation of such systems. The purpose of this research is to explore the applicability of Smart Systems in UK food manufacturing companies, and to identify the key priority areas and improvement levers for the implementation of such systems. A triangulated primary research approach is adopted that includes a questionnaire, follow-up interviews, and visits to 32 food manufacturing companies in the UK. The questionnaire and interviews are guided by a unique measuring instrument that the authors developed that focusses upon SS technologies and systems. This paper makes an original contribution in that it is one of the few academic studies to explore the implementation of SS in the industry, and provides a new perspective on the key drivers and inhibitors of its implementation. The findings suggest that the current turbulence in the industry could be bringing food companies closer to the adoption of such systems, hence, it is a good time to define and develop the optimum SS implementation strategy.

The Internet of things(IoT) is now considered among the most emerging technologies aiming to interconnect heterogeneous smart devices in several areas without human interaction . From sensing and identification to data processing and storing. The Building and the monitoring of smart systems like smart homes, smart campus and smart cities pass through several stages on which different tools and platforms coexist to answer this need. In this paper, we present a survey on recent works using IoT tools to build their systems. Particularly, we classify and compare them according to layers and characteristics that we have defined such as data acquisition, data processing , software used, conformity to standards. Hence , our study aims to provide a clear vision on available functionalities during the process of building IoT systems based on most used IoT tools and to help users to choose the most adapted tool depending on their needs.

The paper summarizes a bottom-up modeling and simulation methodology that starts from heterogeneous models written in heterogeneous languages and it composes them into a homogenous system-level description by exploiting automatic translation and abstraction. This allows the designer to work with his/her favorite design language for representing the heterogeneous behaviors of an embedded system (digital hw, analog hw, software, network, environment, …), but these heterogeneous low level descriptions can be abstracted into a homogeneous system level model for verification, design space exploration, extra-functional properties validation, etc. This huge heterogeneity is particularly evident in smart systems, to whom the methodology has been effectively applied.

This article presents the concepts, the organisation, and the preliminary application results of SMAC, a Smart Systems co-design platform. The SMAC platform, which has been developed as Integrated Project (IP) of the 7th ICT Call under the Objective 3.2 "Smart components and Smart Systems integration" addresses the challenges of the integration of heterogeneous and conflicting domains that emerge in the design of Smart Systems. SMAC includes methodologies and EDA tools enabling multi-disciplinary and multi-scale modelling and design, simulation of multi-domain systems, subsystems and components at different levels of abstraction, system integration and exploration for optimization of functional and non-functional metrics. The article presents the preliminary results obtained by adopting the SMAC platform for the design of a limb tracking smart system.

Complex “smart” devices made of heterogeneous components and incorporating functions of sensing, actuation and control are increasingly requested, but, for the development of next generation systems, new techniques are required for managing the increasing design complexity. The SMAC Project aims at developing a common solution for Smart System design where cross-sectional flows converge into a common Platform, based on (co-)simulation and model abstraction methodologies. This paper describes the main requirements and features of the SMAC Platform and two industrial case studies.

Part 17: Power Conversion; International audience; The emerging of collective awareness platforms opened a new range of driven forces that will converge to more sustainable systems. To achieve this task, these platforms have to support an increasing number of more sophisticated remote sensors and actuators that will need to cooperate smartly and strongly with each other in a mesh type of intelligent interconnectivity. These remote smart miniaturized nodes can add noninvasive intelligence but suffer from lifetime performance due to the small quantity of energy available in micro batteries. Therefore, harvesting energy from the environment is a promising technique. This work presents the study and experimental evaluation of a flexible piezoelectric material to validate the use of a piezoelectric harvester in a CMOS wireless actuator/sensor node.