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Sensor Technologies: Healthcare, Wellness and Environmental Applications

Sensor Technologies: Healthcare, Wellness and Environmental Applications (Paperback)

(Healthcare, Wellness and Environmental Applications)

Michael McGrath, Dawn Nafus, Cliodh Ni Scanaill (지은이)
Apress
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Sensor Technologies: Healthcare, Wellness and Environmental Applications
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· 제목 : Sensor Technologies: Healthcare, Wellness and Environmental Applications (Paperback) (Healthcare, Wellness and Environmental Applications)
· 분류 : 외국도서 > 컴퓨터 > 하드웨어 > 일반
· ISBN : 9781430260134
· 쪽수 : 336쪽
· 출판일 : 2013-12-21

목차

Chapter One: Introduction Chapter Goal: Reader should understand the key challenges and drivers for sensor application development. The reader should also understand how sensor technologies can play a role in addressing some of the key challenges facing global society in the short to medium term. 1. Book overview 2. Drivers for Sensor Applications (Infrastructure Growth in Developing Countries, Advances in Energy Harvesting, New Applications, Cost reduction, Real-time monitoring of situations to avoid unplanned downtime, Security (personal and national), the internet of things). 3. Challenges for Sensor Applications (Power, Efficient Operation in Harsh Environments, Number of Deployable Nodes, Safety and Regulations, High Cost of Installation, Security and Reliability, sensor management) 4. Global Megatrends and the opportunities for sensing technologies o Water and Food Constraints o Aging Demographics o Public Health o Pandemics o Security Chapter 2: Sensing and Sensor Fundamentals Chapter Goal: Reader should understand existing sensor technologies, which can be used in healthcare, wellness, and environmental domains. They should also understand the role of smart sensors and smart phones as mobile sensing platforms and aggregators. 1. Sensing Modalities (Mechanical, MEMS, Optical, ISFET, μTAS) 2. Sensing Domains (Air, Water, Noise, Bacterial, Chemical, Kinematic, DNA, Physiological) 3. Functional Characterisation of Sensors o Communication methods - discrete, wired, wireless o Smart Sensors and Sensor Platforms MSP430 (SHIMMER and telosB motes) ATmega PIC 4. Smart Phones as mobile sensor platforms 5. Selecting and specifying sensors Chapter 3 Key Sensor Technology Components - Hardware and Software Overview Chapter Goal: Reader should have a high level understanding of the key hardware and software components, which are necessary for the development of sensors systems and why technologies are selected for specific applications. 1. Overview - Sensor systems 2. MCU's (TI MSP430, ATmega, PIC) a. ADCs b. Interrupts c. Real-time Clocks 3. Sensor Interfaces a. Digital b. Analog c. I2C 4. Communications - wired and wireless interfaces RS232/485, USB, Ethernet, FieldbusProprietary Short Range Wireless Protocols (e.g. ANT, BodyLAN, Sensium)Standard Short Range Protocols i. IEEE 802.15.6 ii. Bluetooth/Smart Bluetooth iii. 802.15.4 iv. UWB Medium Range i. Wi-Fi 5. Data storage (EEPROM, sd card, data forwarding) 6. Power management and Energy Harvesting 7. Operating Systems and Software Development Environments (SDK's) Chapter 4 Sensor Network Architectures Chapter Goal: Reader should understand the various approaches to the design of sensor network architectures; scaling from body worn systems, to ambient sensing, to city-scale deployments. The reader should also understand the advantages and disadvantages of current and evolving sensor network architectures. 1. Sensor network architectures o Discrete Sensor o Sensor to aggregator o PAN/WPAN/smart clothing o Pervasive/Ambient sensor networks o Wide area networks (city-wide, country wide) 2. Challenges in developing and deploying sensor networks 3. Current and Proposed Solutions o Remote sensor management o Edge Processing o Power harvesting o New communication standards Chapter 5: Adding Vibrancy to Sensor Data Chapter Goal: Reader should understand the various methods to interpret and display sensor data to the user. They will understand the importance of creating a data analysis plan from the outset, and the different types of data analysis throughout the application stack. 1. Data Literacy - How can we intuitively answer questions with sensor data and contextualise answers 2. Data Quality a. Calibration b. Trust and Repudiation 3. Sensor Fusion - combining sensory data from disparate sources 4. Data Mining 5. Data Visualisation 6. Openness, data integration, virtual sensors 7. Exploiting the power of the cloud Chapter 6: Regulation and Standards Chapter G

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