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The paper aims to promote the development of intelligent materials and the 4D printing technology by introducing recent advances and applications of additive layered manufacturing (ALM) technology of intelligent materials and the development of the 4D printing technology. Also, an arm-type ALM technology of shape memory polymer (SMP) with thermosetting polyurethane is briefly introduced.

This paper begins with an overview of the development and applications of intelligent materials around the world and the 4D printing technology. Then, the authors provide a brief outline of their research on arm-type ALM technology of SMP with thermosetting polyurethane.

The paper provides the recent developments and applications of intelligent materials and 4D printing technology. Then, it is suggested that intelligent materials mixed with different functional materials will be developed, and these types of materials will be more suitable for 4D printing.

This paper overviews the current developments and applications of intelligent materials and its use in 4D printing technology, and briefly states the authors’ research on arm-type ALM technology of SMP with thermosetting polyurethane.

The proliferation of customer-related data provides companies with numerous service opportunities to create customer value. The purpose of this study is to develop a framework to use this data to provide services.

This study conducted four action research projects on the use of customer-related data for service design with industry and government. Based on these projects, a practical framework was designed, applied, and validated, and was further refined by analyzing relevant service cases and incorporating the service and operations management literature.

The proposed customer process management (CPM) framework suggests steps a service provider can take when providing information to its customers to improve their processes and create more value-in-use by using data related to their processes. The applicability of this framework is illustrated using real examples from the action research projects and relevant literature.

“Using data to advance service” is a critical and timely research topic in the service literature. This study develops an original, specific framework for a company’s use of customer-related data to advance its services and create customer value. Moreover, the four projects with industry and government are early CPM case studies with real data.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

The future construction site will be pervasive, context aware and embedded with intelligence. The purpose of this paper is to explore and define the concept of the digital skin of the future smart construction site.

The paper provides a systematic and hierarchical classification of 114 articles from both industry and academia on the digital skin concept and evaluates them. The hierarchical classification is based on application areas relevant to construction, such as augmented reality, building information model-based visualisation, labour tracking, supply chain tracking, safety management, mobile equipment tracking and schedule and progress monitoring. Evaluations of the research papers were conducted based on three pillars: validation of technological feasibility, onsite application and user acceptance testing.

Technologies learned about in the literature review enabled the envisaging of the pervasive construction site of the future. The paper presents scenarios for the future context-aware construction site, including the construction worker, construction procurement management and future real-time safety management systems.

Based on the gaps identified by the review in the body of knowledge and on a broader analysis of technology diffusion, the paper highlights the research challenges to be overcome in the advent of digital skin. The paper recommends that researchers follow a coherent process for smart technology design, development and implementation in order to achieve this vision for the construction industry.

Modern meat processing requires automation and robotisation to remain sustainable and adapt to future challenges, including those brought by global infection events. Automation of all or many processes is seen as the way forward, with robots performing various tasks instead of people. Meat cutting is one of these tasks. Smart novel solutions, including smart knives, are required, with the smart knife being able to analyse and predict the meat it cuts. This paper aims to review technologies with the potential to be used as a so-called “smart knife” The criteria for a smart knife are also defined.

This paper reviews various technologies that can be used, either alone or in combination, for developing a future smart knife for robotic meat cutting, with possibilities for their integration into automatic meat processing. Optical methods, Near Infra-Red spectroscopy, electrical impedance spectroscopy, force sensing and electromagnetic wave-based sensing approaches are assessed against the defined criteria for a smart knife.

Optical methods are well established for meat quality and composition characterisation but lack speed and robustness for real-time use as part of a cutting tool. Combining these methods with artificial intelligence (AI) could improve the performance. Methods, such as electrical impedance measurements and rapid evaporative ionisation mass spectrometry, are invasive and not suitable in meat processing since they damage the meat. One attractive option is using athermal electromagnetic waves, although no commercially developed solutions exist that are readily adaptable to produce a smart knife with proven functionality, robustness or reliability.

This paper critically reviews and assesses a range of sensing technologies with very specific requirements: to be compatible with robotic assisted cutting in the meat industry. The concept of a smart knife that can benefit from these technologies to provide a real-time “feeling feedback” to the robot is at the centre of the discussion.

The purpose of this paper is to characterize distracted driving by quantifying the response time and response intensity to an emergency stop using the driver’s physiological states.

Field tests with 17 participants were conducted in the connected and automated vehicle test field. All participants were required to prioritize their primary driving tasks while a secondary nondriving task was asked to be executed. Demographic data, vehicle trajectory data and various physiological data were recorded through a biosignalsplux signal data acquisition toolkit, such as electrocardiograph for heart rate, electromyography for muscle strength, electrodermal activity for skin conductance and force-sensing resistor for braking pressure.

This study quantified the psychophysiological responses of the driver who returns to the primary driving task from the secondary nondriving task when an emergency occurs. The results provided a prototype analysis of the time required for making a decision in the context of advanced driver assistance systems or for rebuilding the situational awareness in future automated vehicles when a driver’s take-over maneuver is needed.

The hypothesis is that the secondary task will result in a higher mental workload and a prolonged reaction time. Therefore, the driver states in distracted driving are significantly different than in regular driving, the physiological signal improves measuring the brake response time and distraction levels and brake intensity can be expressed as functions of driver demographics. To the best of the authors’ knowledge, this is the first study using psychophysiological measures to quantify a driver’s response to an emergency stop during distracted driving.

The purpose of this paper was to investigate whether small holes in an impermeable patch at the wrist improve perceived comfort during exercise.

Nine male participants participated in this study. During the experiment, participants cycled 60 W in a hot room (35°C, 30 percent relative humidity) while an impermeable 20 cm² patch was located on the ventral side of one wrist and at the same time a patch of identical shape with 5 mm diameter holes (17.7 percent uncovered) on the other wrist. The participants could not see the patches. Participants were forced to choose which patch they perceived as more comfortable. Chest and arm skin temperature, thermal comfort, thermal sensation and wetness perception were assessed.

Participants preferred 5 mm holes over no holes (p=0.017). Chest skin temperature (p=0.018) but not arm skin temperature correlates with this preference. Thermal comfort, thermal sensation and wetness perception did not differ significantly between patches. It is concluded that patches with 5 mm holes are preferred over impermeable patches during work in the heat in particular when the torso skin is warm.

The wrist is a preferred location for smart wearables. Generally, wrist bands are made of air-impermeable materials leading to sensation of wetness and discomfort. This study has shown that manufacturers should consider to make small holes in their wrist bands to optimize wearing comfort.

This paper aims to describe the mechanical aspects of unmanned Mothership Plane and Sensing Drones. The presented conceptual system shows the idea and possible way of designing different sizes and objective systems based on experience gained during the SAE Aero Design Competition.

The UAS is based on a SAE Aero Design Competition designed and manufactured Mothership Plane converted to a high endurance platform modified to launch up to six small copters. The process of designing and converting the Mothership is described. The methodology of selecting and planning either the structure or hardware of the drones is presented.

A key finding is that the presented conception of mothership plane deploying in flight a group of small sensing multirotors is achievable. Moreover, the modular build of the system provides the possibility to adapt currently existing unmanned aircrafts to be converted to the described mothership plane.

To conduct flight tests and to study encountered problems. Presentation of the unmanned aerial system (UAS) concept that can be used to scan an area and create 3D maps for Search and Rescue missions as well as agriculture applications.

The paper describes the conceptual approach to design a UAS consisting of the mothership plane and the sensing drones. The paper highlights the potential solutions gained by using such a UAS. The focus is to present a technology and system that can perform real time observations in widespread and difficult to reach areas.

This study aims to explore how people bodily narrate and use collective memory to clarify their embodied experiences regarding a city which they memorise.

Drawing on 1,359 short stories collected by the online travel portal Visit Turku about ‘How the city feels’, the fine-grained embodied experiences of people are represented through descriptions of their feelings towards the city of Turku.

Based on the analysis, two aspects through which the respondents narrated their embodied experiences of cities have been identified: (1) the sociomaterial entanglements with the city and (2) the humane relationship with the city.

This study is limited to short stories acquired online, raising questions of anonymity and representativeness. Thus, these narrations are constructions which have to be interpreted as told by specific people in a certain time and place.

Tourist agencies should pay attention to the value of looking at written stories as bodily materialisations of people’s experiences of city destinations. Understanding this would strengthen the cities’ competitiveness.

By empirically highlighting how people memorise a city through narrations, the study offers novel viewpoints on the embodied experiences in cities as well as the cultural constructs these narrations are based on, thus broadening our understanding of how cities become bodily entangled with us.

The authors aim to develop a conceptual framework for longitudinal estimation of stress-related states in the wild (IW), based on the machine learning (ML) algorithms that use physiological and non-physiological bio-sensor data.

The authors propose a conceptual framework for longitudinal estimation of stress-related states consisting of four blocks: (1) identification; (2) validation; (3) measurement and (4) visualization. The authors implement each step of the proposed conceptual framework, using the example of Gaussian mixture model (GMM) and K-means algorithm. These ML algorithms are trained on the data of 18 workers from the public administration sector who wore biometric devices for about two months.

The authors confirm the convergent validity of a proposed conceptual framework IW. Empirical data analysis suggests that two-cluster models achieve five-fold cross-validation accuracy exceeding 70% in identifying stress. Coefficient of accuracy decreases for three-cluster models achieving around 45%. The authors conclude that identification models may serve to derive longitudinal stress-related measures.

Proposed conceptual framework may guide researchers in creating validated stress-related indicators. At the same time, physiological sensing of stress through identification models is limited because of subject-specific reactions to stressors.

Longitudinal indicators on stress allow estimation of long-term impact coming from external environment on stress-related states. Such stress-related indicators can become an integral part of mobile/web/computer applications supporting stress management programs.

Timely identification of excessive stress may improve individual well-being and prevent development stress-related diseases.

The study develops a novel conceptual framework for longitudinal estimation of stress-related states using physiological and non-physiological bio-sensor data, given that scientific knowledge on validated longitudinal indicators of stress is in emergent state.