Static Human Detection and Scenario Recognition via Wearable Thermal Sensing System

Conventional wearable sensors are mainly used to detect the physiological and activity information of individuals who wear them, but fail to perceive the information of the surrounding environment. This paper presents a wearable thermal sensing system to detect and perceive the information of surrounding human subjects. The proposed system is developed based on a pyroelectric infrared sensor. Such a sensor system aims to provide surrounding information to blind people and people with weak visual capability to help them adapt to the environment and avoid collision. In order to achieve this goal, a low-cost, low-data-throughput binary sampling and analyzing scheme is proposed. We also developed a conditioning sensing circuit with a low-noise signal amplifier and programmable system on chip (PSoC) to adjust the amplification gain. Three statistical features in information space are extracted to recognize static humans and human scenarios in indoor environments. The results demonstrate that the proposed wearable thermal sensing system and binary statistical analysis method are efficient in static human detection and human scenario perception

Towards optimal sensor deployment for location tracking in smart home

International audienceAmbient Assisted Living (AAL) aims to ease the daily living and working environmentfor disabled/elderly peopleat home. AAL use information and communication technology based on sensors data. These sensors are generally placed randomly without taking into account the layout of buildings and rooms. In this paper, we develop a mathematical model foroptimal sensor placement in order (i) to optimize the sensor number with regard to room features, (ii) to ensure a reliability level in sensor networkconsidering a sensor failure rate. This placement ensures the targettracking in smart home sinceoptimizing sensorplacement allow us to distinguish different zonesand consequently, to identify the target location, according to the activated sensors

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts

The NASA SBIR product catalog

The purpose of this catalog is to assist small business firms in making the community aware of products emerging from their efforts in the Small Business Innovation Research (SBIR) program. It contains descriptions of some products that have advanced into Phase 3 and others that are identified as prospective products. Both lists of products in this catalog are based on information supplied by NASA SBIR contractors in responding to an invitation to be represented in this document. Generally, all products suggested by the small firms were included in order to meet the goals of information exchange for SBIR results. Of the 444 SBIR contractors NASA queried, 137 provided information on 219 products. The catalog presents the product information in the technology areas listed in the table of contents. Within each area, the products are listed in alphabetical order by product name and are given identifying numbers. Also included is an alphabetical listing of the companies that have products described. This listing cross-references the product list and provides information on the business activity of each firm. In addition, there are three indexes: one a list of firms by states, one that lists the products according to NASA Centers that managed the SBIR projects, and one that lists the products by the relevant Technical Topics utilized in NASA's annual program solicitation under which each SBIR project was selected

Multimodal radar sensing for ambient assisted living

Data acquired from health and behavioural monitoring of daily life activities can be exploited to provide real-time medical and nursing service with affordable cost and higher efficiency. A variety of sensing technologies for this purpose have been developed and presented in the literature, for instance, wearable IMU (Inertial Measurement Unit) to measure acceleration and angular speed of the person, cameras to record the images or video sequence, PIR (Pyroelectric infrared) sensor to detect the presence of the person based on Pyroelectric Effect, and radar to estimate distance and radial velocity of the person. Each sensing technology has pros and cons, and may not be optimal for the tasks. It is possible to leverage the strength of all these sensors through information fusion in a multimodal fashion. The fusion can take place at three different levels, namely, i) signal level where commensurate data are combined, ii) feature level where feature vectors of different sensors are concatenated and iii) decision level where confidence level or prediction label of classifiers are used to generate a new output. For each level, there are different fusion algorithms, the key challenge here is mainly on choosing the best existing fusion algorithm and developing novel fusion algorithms that more suitable for the current application. The fundamental contribution of this thesis is therefore exploring possible information fusion between radar, primarily FMCW (Frequency Modulated Continuous Wave) radar, and wearable IMU, between distributed radar sensors, and between UWB impulse radar and pressure sensor array. The objective is to sense and classify daily activities patterns, gait styles and micro-gestures as well as producing early warnings of high-risk events such as falls. Initially, only “snapshot” activities (single activity within a short X-s measurement) have been collected and analysed for verifying the accuracy improvement due to information fusion. Then continuous activities (activities that are performed one after another with random duration and transitions) have been collected to simulate the real-world case scenario. To overcome the drawbacks of conventional sliding-window approach on continuous data, a Bi-LSTM (Bidirectional Long Short-Term Memory) network is proposed to identify the transitions of daily activities. Meanwhile, a hybrid fusion framework is presented to exploit the power of soft and hard fusion. Moreover, a trilateration-based signal level fusion method has been successfully applied on the range information of three UWB (Ultra-wideband) impulse radar and the results show comparable performance as using micro-Doppler signature, at the price of much less computation loads. For classifying ‘snapshot’ activities, fusion between radar and wearable shows approximately 12% accuracy improvement compared to using radar only, whereas for classifying continuous activities and gaits, our proposed hybrid fusion and trilateration-based signal level improves roughly 6.8% (before 89%, after 95.8%) and 7.3% (before 85.4%, after 92.7%), respectively

Monitoring of urban transportation networks using wireless sensor networks

Dissertação de mestrado, Engenharia Informática, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015With today’s technologies, constant growth of people in major cities and the permanent concern with our natural resources, such as energy, it is inevitable that we look for ways to improve our urban transportation networks. One way of improving transportation networks is to make an efficient vehicle routing. In this thesis vehicle routing with backup provisioning, using wireless sensor technologies, is proposed. We start by collecting the entry and exit of people inside urban transportations, which will give us a view of fleet load over time, using wireless sensor technologies. For this purpose a monitoring software was developed. Such data gathering and monitoring tool will allow data analysis in real time and, according to information extracted, to propose solutions for service improvements. In this thesis the possibility of using such data to plan vehicle routes with backup provisioning is discussed. That is, a variant of the open vehicle routing problem is proposed, called vehicle routing with backup provisioning, where the possibility of reacting to overloading/overcrowding of vehicles in certain stops is considered. After mathematically formalizing the problem a heuristic algorithm to plan routes is proposed. Results show that vehicle routing with backup provisioning can be a way of providing sustainable urban mobility with efficient use of resources, while increasing quality of service perceived by users. We expect this tool to be useful for the improvement of Urban Transportation Networks

Distributed Architectures for Intensive Urban Computing: A Case Study on Smart Lighting for Sustainable Cities

New information and communication technologies have contributed to the development of the smart city concept. On a physical level, this paradigm is characterized by deploying a substantial number of different devices that can sense their surroundings and generate a large amount of data. The most typical case is image and video acquisition sensors. Recently, these types of sensors are found in abundance in urban spaces and are responsible for producing a large volume of multimedia data. The advanced computer vision methods for this type of multimedia information means that many aspects can be dynamically monitored, which can help implement value-added applications in the city. However, obtaining more elaborate semantic information from these data poses significant challenges related to a large amount of data generated and the processing capabilities required. This paper aims to address these issues by using a combination of cloud computing technologies and mobile computing techniques to design a three-layer distributed architecture for intensive urban computing. The approach consists of distributing the processing tasks among a city’s multimedia acquisition devices, a middle computing layer, known as a cloudlet, and a cloud-computing infrastructure. As a result, each part of the architecture can now focus on a small number of tasks for which they are specially designed, and data transmission communication needs are significantly reduced. To this end, the cloud server can hold and centralize the multimedia analysis of the processed results from the lower layers. Finally, a case study on smart lighting is described to illustrate the benefits of using the proposed model in smart city environments.This work was supported in part by the Spanish Research Agency (AEI) and the European Regional Development Fund (FEDER) through the project CloudDriver4Industry under Grant TIN2017-89266-R, in part by the Spanish Ministry of Science, Innovation and Universities through the Project ECLIPSE-UA under Grant RTI2018-094283-B-C32, and in part by the Conselleria de Educación, Investigación, Cultura y Deporte of the Community of Valencia, Spain, within the Program of Support for Research under Project AICO/2017/134 and Project PROMETEO/2018/089

Human and Biological Skin-Inspired Electronic Skins for Advanced Sensory Functions and Multifunctionality

Department of Energy Engineering (Energy Engineering)The electronic skin (e-skin) technology is an exciting frontier to drive next generation of wearable electronics owing to its high level of wearability to curved human body, enabling high accuracy to harvest information of users and their surroundings. Altough various types of e-skins, based on several signal-transduction modes, including piezoresistive, capacitive, piezoelectric, triboelectric modes, have been developed, their performances (i.e. sensitivity, working range, linearity, multifunctionality, etc.) should be improved for the wearable applications. Recently, biomimicry of the human and biological skins has become a great inspiration for realizing novel wearable e-skin systems with exceptional multifunctionality as well as advanced sensory functions. As an ideal sensory organ, tactile sensing capabilities of human skin was emulated for the development of e-skins with enhanced sensor performances. In particular, the unique geometry and systematic sensory system of human skin have driven new opportunities in multifunctional and highly sensitive e-skin applications. In addition, extraordinary architectures for protection, locomotion, risk indication, and camouflage in biological systems provide great possibilities for second skin applications on user-interactive, skin-attachable, and ultrasensitive e-skins, as well as soft robots. Benefitting from their superior perceptive functions and multifunctionality, human and biological skins-inspired e-skins can be considered to be promising candidates for wearable device applications, such as body motion tracking, healthcare devices, acoustic sensor, and human machine interfaces (HMI). This thesis covers our recent studies about human and biological skin-inspired e-skins for advanced sensory functions and multifunctionality. First, chapter 1 highlights various types of e-skins and recent research trends in bioinspired e-skins mimicking perceptive features of human and biological skins. In chapter 2, we demonstrate highly sensitive and tactile-direction-sensitive e-skin based on human skin-inspired interlocked microdome structures. Owing to the stress concentration effect, the interlocked e-skin experiences significant change of contact area between the interlocked microdomes, resulting in high pressure sensitivity. In addition, because of the different deformation trends between microstructures in mutual contact, the interlocked e-skin can differentiate and decouple sensor signals under different directional forces, such as pressure, tensile strain, shear, and bending. In chapter 3, interlocked e-skins were designed with multilayered geometry. Although interlocked e-skin shows highly sensitive pressure sensing performances, their pressure sensing range is narrow and pressure sensitivity continuously decreases with increasing pressure level. The multilayer interlocked microdome geometry can enhance the pressure-sensing performances of e-skins, such as sensitivity, working range, and linearity. As another approach of e-skin with multilayered geometry, we demonstrate multilayered e-skin based on conductivity-gradient conductive materials in chapter 4. The conducive polymer composites with different conductivity were coated on the microdome pattern and designed as interlocked e-skin with coplanar electrode design, resulting in exceptionally high pressure-sensing performances compared with previous literatures. In chapter 5, inspired by responsive color change in biological skins, we developed mechanochromic e-skin with a hierarchical nanoparticle-in-micropore architecture. The novel design of hierarchical structure enables effective stress concentration at the interface between nanoparticle and porous structure, resulting in impressive color change under mechanical stimuli. In chapter 6, we emulate ultrahigh temperature sensitivity of human and snake skin for temperature-sensitive e-skin. The thermoresponsive composite based on semi-crystalline polymer, temperature sensor shows ultrahigh temperature sensitivity near the melting point of semi-crystalline polymer. In addition, integration of thermochromic composite, mimicking biological skins, enables dual-mode temperature sensors by electrical and colorimetric sensing capabilities. Finally, in chapter 7, we summarize this thesis along with future perspective that should be considered for next-generation e-skin electronics. Our e-skins, inspired by human and biological skin, can provide a new paradigm for realizing novel wearable electronic systems with exceptional multifunctionality as well as advanced sensory functions.clos

Engineering derivatives from biological systems for advanced aerospace applications

The present study consisted of a literature survey, a survey of researchers, and a workshop on bionics. These tasks produced an extensive annotated bibliography of bionics research (282 citations), a directory of bionics researchers, and a workshop report on specific bionics research topics applicable to space technology. These deliverables are included as Appendix A, Appendix B, and Section 5.0, respectively. To provide organization to this highly interdisciplinary field and to serve as a guide for interested researchers, we have also prepared a taxonomy or classification of the various subelements of natural engineering systems. Finally, we have synthesized the results of the various components of this study into a discussion of the most promising opportunities for accelerated research, seeking solutions which apply engineering principles from natural systems to advanced aerospace problems. A discussion of opportunities within the areas of materials, structures, sensors, information processing, robotics, autonomous systems, life support systems, and aeronautics is given. Following the conclusions are six discipline summaries that highlight the potential benefits of research in these areas for NASA's space technology programs

Artificial Intelligence and Cognitive Computing

Artificial intelligence (AI) is a subject garnering increasing attention in both academia and the industry today. The understanding is that AI-enhanced methods and techniques create a variety of opportunities related to improving basic and advanced business functions, including production processes, logistics, financial management and others. As this collection demonstrates, AI-enhanced tools and methods tend to offer more precise results in the fields of engineering, financial accounting, tourism, air-pollution management and many more. The objective of this collection is to bring these topics together to offer the reader a useful primer on how AI-enhanced tools and applications can be of use in today’s world. In the context of the frequently fearful, skeptical and emotion-laden debates on AI and its value added, this volume promotes a positive perspective on AI and its impact on society. AI is a part of a broader ecosystem of sophisticated tools, techniques and technologies, and therefore, it is not immune to developments in that ecosystem. It is thus imperative that inter- and multidisciplinary research on AI and its ecosystem is encouraged. This collection contributes to that