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Outlines the current research work on intelligent sensors and intelligent transducers which will be required in complex systems. Discusses the elements of an intelligent sensor and concludes that these require analogue filtering, data conversion and compensation, and a digital communication link to a common signal bus. Explains what is meant by a systems approach to intelligent sensors with layered information processing. Concludes that unless a deeper understanding of the basics of sensor systems is acquired new intelligent sensor design will be very difficult.

Describes the improvements that smart sensors will bring to electronic measurement and control systems, and the advantages of using integrated sensors. Outlines the problems encountered when designing integrating electronics for use on a smart sensor chip and lists the major functions that smart sensors must perform. Concludes that the solution to many real life sensor problems will only be found when a well designed “care‐free” intelligent sensor can be produced and continues that the way to realize this concept is to combine a sensor device with a number of micro‐electronic components into a single sensor package.

This paper aims to define imminent and future key aspects in innovative production machines and systems but more specifically to focus on the automation and control aspects.

The foresight analysis is based on the state‐of‐the‐art of current manufacturing technologies with a setup of key enabling features and a roadmap research.

The paper finds that more integration of current and future technology development is required to build a strong platform for various applications featured with interoperability, trust, security and protection. Autonomy and close collaboration aspects in machines remain as crucial targets for the near future. An immediate action is required on smart strategies for the design patterns and agents to enable intuitive components for high quality dynamic user interfaces. This will allow rapid configuration and adaptation to new manufacturing tasks with highly improved machine learning.

The paper describes the future of key aspects required to move the production, automation and control systems forward.

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.

This paper aims to serve two main purposes. In the first instance it aims to it provide an overview addressing the state‐of‐the‐art in the area of activity recognition, in particular, in the area of object‐based activity recognition. This will provide the necessary material to inform relevant research communities of the latest developments in this area in addition to providing a reference for researchers and system developers who ware working towards the design and development of activity‐based context aware applications. In the second instance this paper introduces a novel approach to activity recognition based on the use of ontological modeling, representation and reasoning, aiming to consolidate and improve existing approaches in terms of scalability, applicability and easy‐of‐use.

The paper initially reviews the existing approaches and algorithms, which have been used for activity recognition in a number of related areas. From each of these, their strengths and weaknesses are discussed with particular emphasis being placed on the application domain of sensor enabled intelligent pervasive environments. Based on an analysis of existing solutions, the paper then proposes an integrated ontology‐based approach to activity recognition. The proposed approach adopts ontologies for modeling sensors, objects and activities, and exploits logical semantic reasoning for the purposes of activity recognition. This enables incremental progressive activity recognition at both coarse‐grained and fine‐grained levels. The approach has been considered within the realms of a real world activity recognition scenario in the context of assisted living within Smart Home environments.

Existing activity recognition methods are mainly based on probabilistic reasoning, which inherently suffer from a number of limitations such as ad hoc static models, data scarcity and scalability. Analysis of the state‐of‐the‐art has helped to identify a major gap between existing approaches and the need for novel recognition approaches posed by the emerging multimodal sensor technologies and context‐aware personalised activity‐based applications in intelligent pervasive environments. The proposed ontology based approach to activity recognition is believed to be the first of its kind, which provides an integrated framework‐based on the unified conceptual backbone, i.e. activity ontologies, addressing the lifecycle of activity recognition. The approach allows easy incorporation of domain knowledge and machine understandability, which facilitates interoperability, reusability and intelligent processing at a higher level of automation.

The comprehensive overview and critiques on existing work on activity recognition provide a valuable reference for researchers and system developers in related research communities. The proposed ontology‐based approach to activity recognition, in particular the recognition algorithm has been built on description logic based semantic reasoning and offers a promising alternative to traditional probabilistic methods. In addition, activities of daily living (ADL) activity ontologies in the context of smart homes have not been, to the best of one's knowledge, been produced elsewhere.

This paper aims to study different possibilities for implementing easy-to-use and cost-effective micro-systems to detect and trace expelled gases from rotten food. The paper covers various radio-frequency identification (RFID) technologies and gas sensors as the two promoting feasibilities for the tracing of packaged food. Monitoring and maintaining quality and safety of food in transport and storage from producer to consumer are the most important concerns in food industry. Many toxin gases, even in parts per billion ranges, are produced from corrupted and rotten food and can endanger the consumers’ health. To overcome the issues, intelligent traceability of food products, specifically the packaged ones, in terms of temperature, humidity, atmospheric conditions, etc., has been paid attention to by many researchers.

Food poisoning is a serious problem that affects thousands of people every year. Poisoning food must be recognized early to prevent a serious health problem.

Contaminated food is usually detectable by odor. A small gas sensors and low-cost tailored to the type of food packaging and a communication device for transmitting alarm output to the consumer are key factors in achieving intelligent packaging.

Conducting polymer composite, intrinsically conducting polymer and metal oxide conductivity gas sensors, metal–oxide–semiconductor field-effect transistor (MOSFET) gas sensors offer excellent discrimination and lead the way for a new generation of “smart sensors” which will mould the future commercial markets for gas sensors.

Small size, low power consumption, short response time, wide operating temperature, high efficiency and small area are most important features of introduced system for using in package food.

Intelligent lighting control system can control lights to go off when people leave, which has been widely concerned by researchers.

In this study, an intelligent lighting control system based on wireless sensor network was designed. First, the hardware and software designs of the system were described briefly. Then, the lighting control algorithm was analyzed emphatically. Considering the illumination and uniformity of light, an intelligent lighting control algorithm based on gradient descent was designed.

In the system test, it was found that the system had a good through-wall communication function, and the communication distance could fully meet the system requirements and run normally. In the test of the lighting control algorithm, it was found that the user’s satisfaction on uniformity in different scenarios was close to 1, and the satisfaction on illumination could also meet the user’s needs, which verified the reliability of the lighting control algorithm.

This study provides some theoretical supports for the better application of wireless sensor network in intelligent light control system, which is conducive to the further development of light control system.

The aim of this paper is threefold: first, to review the technological state of the art on tire sensor systems; second, to summarize basic methodologies and explore the potential of tire sensing for intelligent vehicle developments and third, to address challenges in the development of tire sensing systems and inspire future research in this field.

Nowadays, automotive industry is moving toward an intelligent and autonomous driving era with the assistance of sensing technology development, whereas tire-road conditions sensing and utilization are of great interest from the point of view of vehicle dynamics control, vehicle safety and vehicle performance evaluation.

Tire sensing is an emerging technology whereby sensor systems are installed on the tire to provide fundamental insights into tire-road interactions for ground vehicles and wheel robots. In the past two decades, tire sensing systems based on various sensor types have been proposed to offer the possibility to investigate tire-road interactions.

Instrumenting the tire with sensors, especially accelerometers and optical sensors, can sense the tire-road interactions and enhance the vehicle performance. The harsh environment inside tire cavity requires reliable, accurate, low weight, modularized and inexpensive sensors. Challenges, such as the data transmission, power management, lack of physics-based tire models need to be solved before the tire sensor becomes commercially viable for production vehicles.

The purpose of this paper is to demonstrate a novel 3D system-in-package (SiP) approach. This new packaging approach is based on stacked silicon submount technology. As demonstrators, a smart lighting module and a sensor systems were successfully developed by using the fabrication and assembly process described in this paper.

The stacked module consists of multiple layers of silicon submounts which can be designed and fabricated in parallel. The 3D stacking design offers higher silicon efficiency and miniaturized package form factor. This platform consists of silicon submount design and fabrication, module packaging, system assembling and testing and analyzing.

In this paper, a smart light emitting diode system and sensor system will be described based on stacked silicon submount and 3D SiP technology. The integrated smart lighting module meets the optical requirements of general lighting applications. The developed SiP design is also implemented into the miniaturization of particular matter sensors and gas sensor detection system.

SiP has great potential of integrating multiple components into a single compact package, which has potential implementation in intelligent applications.