Recent years have witnessed the development and proliferation of wireless sensor networks (WSNs), attributed to the technological advances of microelectrome-chanical systems (MEMS) and wireless communications. A WSN is composed of a number of sensor nodes, which are distributed in a specific area to perform certain sensing tasks. A typical sensor node is a low-cost battery-powered device equipped with one or more sensors, a processor, memory, and a short-range wireless transceiver. A variety of sensors, including thermal, optical, magnetic, acoustic, and visual sensors, are used to monitor different properties of the environment. The processor and memory enable the sensor node to perform simple data processing and storing operations. The transceiver makes the sensor node capable of wireless communications, which is critical for WSNs. With many WSNs located in difficult-to-access areas, users usually cannot collect the data in sensor nodes directly. In this case, sensors nodes can transmit the data through the wireless channel to the user or the data sink either directly or by relaying through multiple sensor nodes. Due to the same geographical difficulty, the batteries, as the power supply of the sensor nodes, are difficult to recharge or replace, restricting nodes' energy budget. Therefore, energy efficiency is the primary design concern in many WSNs.

关键词：光机电；传感器；无线网络；压缩

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In the future, technology will be hidden in the environment and invisible to the user but, at the same time, responsive and adaptive to user interaction and environmental variations [1]. For example, smart buildings will become aware of the presence of people and of their needs: thanks to this, temperature and light conditions will be adapted automatically for the best comfort and optimal power consumption. The realization of such a vision requires a technology that can sense, process and respond to external stimuli, both human and environmental, coming from many spots of a large environment, such as a room, a house or a whole building. An answer to such needs may come from WSNs. These are networks that consist of a large number of energy-autonomous nodes deployed into the environment to collect physical data.

关键词：光机电；传感器；集成；网络收音机

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Precision agriculture can particularly benefit from wireless sensor networks, as they allow continuous and fine-grained monitoring of environmental data, which can thus be used to reduce management costs and improve crop quality. Such applications typically require long-term and unattended monitoring of large geographical areas. Therefore, sensor nodes must be able to self-organize and use their limited energy budget very efficiently, so as to prolong the network lifetime to many months or, even, years. In this chapter we present ASLEEP, an adaptive strategy for efficient power management in multi-hop WSNs targeted to periodic data collection. The proposed strategy dynamically adjusts the active periods of nodes to match the network demands with the minimum energy expenditure. In this chapter we focus on the implementation and the experimental evaluation of ASLEEP on a real testbed deployed in a vineyard, according to the case study considered in the project. We show that our adaptive approach actually reduces the energy consumption of sensor nodes, thus increasing the network lifetime up to several years.

关键词：光机电；传感器；网络监测；实验

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The grasp and the task are two actions closely related. A grasp is always performed with a purpose in mind, and the execution of a task requires a suitable task-oriented grasp in most of the cases. The grasp does not need to be prehensile. Most of our daily life manipulation is done trough non-prehensile grasps. Interaction with the environment is always preceded by a contact configuration, as a result of a prehensile or non-prehensile grasp. And vice versa, a contact configuration on one object is always followed by a desired motion according to the task: lift, push, etc.

关键词：光机电；传感器；物理交互；框架

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This report documents (1) the successful FCC certification effort by AKELA and (2) AKELA user test and evaluation of the NIJ ASTIR system. At the conclusion of this NIJ Cooperative effort, the ASTIR system received final FCC Certification. The FCC certification allows the availability of the ASTIR for LE emergency operations. Its effectiveness will be a function of the building wall material makeup, line-of-site metallic and moving obstructions, and complexity of the building structure. Due to limited user operational testing on complex structures and wall construction materials, it is anticipated that image display information and associated interpretation will require signal processing product improvement. Product improvements will be limited to signal processing and imaging display software - no modifications are required for radar hardware and/or the physical system.

关键词：光机电；传感器；墙成像；FCC认证

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Image sensors have become significant due to the high demand from different applications. Charge-Coupled Device (CCD) and Complementary Metal-Oxide Semiconductor (CMOS) image sensors are two different technologies used for capturing images digitally. Both types of imagers are fabricated in silicon and convert light into electronic signals for processing. Section 3.1 of this chapter discusses briefly the CCDs and CMOS image sensors. Section 3.2 gives an overview of the photodetection in silicon. The different types of photodiodes used to sense the light intensity are discussed. Section 3.3 discusses the basic types of pixels commonly used in CMOS image sensors. The advantages and disadvantages of each type are elaborated. Section 3.4 discusses the performance parameters of the CMOS image sensors and section 3.5 presents the peripheral circuits used in conventional CMOS image sensors. Section 3.6 describes the design of a 128×128 pixel CMOS image sensor chip with in-pixel analog memory and a 1-bit dynamic memory in a standard 0.18μm 1-poly-3-metal CMOS CIS (CMOS Image Sensor) process. The characterization and measurement results of the image sensor are also presented in section 3.7.

关键词：光机电；传感器；CMOS；设计

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Material classification is an important application in computer vision. The ability to detect the nature of the object surface from image data has a very high potential for applications ranging from low-level inspection to high-level object recognition. The inherent property of materials to partially polarize the reflected light can serve as a tool to classify them. In this chapter, an introduction to material classification is presented in section 5.1. The theory behind polarization upon specular reflection and Fresnel coefficients is covered in section 5.2. The Fresnel reflectance model is also briefly described. The polarized nature of the transmitted light can be used to differentiate between metal and dielectric surfaces in real time due to the different nature in partially polarizing the specular and diffuse reflection components of the reflected light. This is elaborated in section 5.3 by measuring the transmitted irradiance after reflection from the material surface which allows computation of Fresnel reflection coefficients, the degree of partial polarization and the variations in the maximum and minimum transmitted intensities for varying specular angle of incidence. Differences in the physical parameters for various metal surfaces result in different surface reflection behavior, influencing the Fresnel reflection coefficients. Section 5.4, shows that it is possible to differentiate among various metals of varying conductivity by sensing the change in the Polarization Fresnel Ratio and the degree of polarization of the light reflected. Section 5.5 presents a short summary of the methods used to differentiate among material surfaces.

关键词：光机电；传感器；CMOS；材料分类

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Since their introduction, Wireless Sensor Networks (WSN) have been proposed as a powerful support for environment monitoring, ranging from monitoring of remote or hard-to-reach locations to fine-grained control of cultivations. Development of a WSN-based application is a complex task and challenging issues must be tackled starting from the first phases of the design cycle. We present here a tool supporting the DSE phase to perform architectural choices for the nodes and network topology, taking into account target performance goals and estimated costs. When designing applications based on WSN, the most challenging problem is energy shortage. Nodes are normally supplied through batteries, hence a limited amount of energy is available and no breakthroughs are foreseen in a near future. In our design cycle we approach this issue through a methodology that allows analysing and optimising the power performances in a hierarchical fashion, encompassing various abstraction levels.

关键词：光机电；传感器；无线网络；优化

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Wireless sensor networks (WSNs) represent a new domain of distributed computing that has attracted great research interest over the last years. A WSN is composed of a large number of tiny battery-operated devices equipped with one or more sensing units, processor, memory, and wireless radio. The main goal of WSNs is to collect data about physical phenomena and deliver them to user applications through one or more exit points called sink nodes. Sink nodes are powerful devices, often a personal computer, that are in charge of gathering all the sensor-collected data, further processing them, and making them available to external networks such as the Internet.

关键词：光机电；传感器；无线网络；能源效率

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Dexterous grasping and manipulation of objects with robot hands requires the ability to monitor contact locations in real-time and with good spatial resolution in order to close the control loop required for object and contact trajectory generation. The ability to recognize incipient slippage will allow for autonomous grasp force adaption - a major prerequisite to handle objects of unknown weight. To provide appropriate tactile sensing capabilities, this paper presents the development of a modular tactile sensor system focusing especially on high frame rates (up to 1.9 kHz) and good spatial resolution (5mm). Larger sensor areas are composed from identical sensor modules providing a 16x16 matrix of tactels. We compare different tactel layouts and force-sensitive materials to achieve optimal sensitivity especially to low forces in order to facilitate detection of first touch. Finally we demonstrate the versatility of the sensor to detect incipient slippage employing a Fourier transformation of the high-frequency tactile signal as input to a multi-layer perceptron, which learns to accomplish the classification tasks.

关键词：光机电；传感器；触觉；检测

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