Sensor Technology. Summer School: Advanced Microsystems Technologies for Sensor Applications

Transcription

1 Sensor Technology Summer School: Universidade Federal do Rio Grande do Sul (UFRGS) Porto Alegre, Brazil July 12 th 31 st,

2 Outline of the Lecture: Philosophy of Sensing Instrumentation and Systems Semiconductor Basics Radiation Sensors Mechanical Sensors Magnetic Sensors Thermal Sensors Chemical Sensors Biological Sensors Environmental Sensor Systems Nanosensors Recitatives 2

3 Introduction: Prediction: (ESNs) will cause a revolution in earth systems research and environmental sciences (similar to the employment of satellites in the 1970s) Imperative needs for the development of ESNs: technological understanding and environmental understanding new technologies new software new large scale models of environmental behavior Many benefits to the society e. g. improvement of public access to pure research e. g. hazard alerts 3

4 Introduction: ESNs array of electronic devices containing (various) sensors ESNs interconnected by using a radio network ESNs allow the investigation of fundamental processes in the environment ESNs provide vital hazard warnings (e. g. flood or tsunami alerts) ESNs particular important in remote (e. g. arctic or antarctic regions) or dangerous environments (e. g. vast nuclear contamination) ESNs give access to information rarely studied in the past Strong emergence of ESNs promoted by progress in technological developments in miniaturization of electronics semiconductor technology computer science wireless communication and internet technologies 4

5 Structure of an ESN: Schematic diagram of an ESN: sensor nodes gather data via a network the data is transferred to one or more base stations base stations forward data to a sensor network server (SNS) the SNS is connected to the world wide web (WWW) public access to information K. Martinez, J. K. Hart, R. Ong, IEEE Computer 37, (2004) 5

6 Sensor Nodes: Scales of sensor nodes J. K. Hart, K. Martinez, Earth-Science Reviews 78, (2006) 6

7 Example of an ESN: GLACSWEB system at Briksdalsbreen (Norway) Custom sensor probes are placed in, on and under glaciers Data collected from sensor probes by a base station on the surface Measurements: temperature pressure subglacial movement weather stress Important for understanding of glaciers dynamics and global warming 7

8 Example of an ESN: GLACSWEB system for the monitoring of the behavior of glaciers (at Briksdalsbreen, Norway) system overview: sensor nodes, envinodes Pressure sensors Temperature sensors Orientation sensors (tilt in three dimensions) 8

9 Example of an ESN: GLACSWEB system (Briksdalsbreen, Norway) Envinode (sensor node) Open Probe (length: 10 cm) Probe measures: pressure temperature orientation K. Martinez, J. K. Hart, R. Ong, IEEE Computer 37, (2004) 9

10 Example of an ESN: GLACSWEB system (Briksdalsbreen, Norway) Envinode System diagram of the probe K. Martinez, J. K. Hart, R. Ong, IEEE Computer 37, (2004) 10

11 Example of an ESN: GLACSWEB system at Briksdalsbreen (Norway) Base station & antenna tripod Vertical pole holds: GPS* GSM** long range antennas snow measuring device * GPS: global positioning system ** GSM:global system for mobile communication 11

12 Example of an ESN: GLACSWEB system (Briksdalsbreen, Norway) Base station: system diagram K. Martinez, J. K. Hart, R. Ong, IEEE Computer 37, (2004) 12

13 Example of an ESN: GLACSWEB system at Briksdalsbreen (Norway) Reference station Fixed point for positioning 13

14 Example of an ESN: GLACSWEB system at Briksdalsbreen (Norway) Example: Pressure (in psi) from a typical Probe over a 8 days period K. Martinez, J. K. Hart, R. Ong, IEEE Computer 37, (2004) 14

15 Example of an ESN: GLACSWEB system at Briksdalsbreen (Norway) Example: Base station battery voltage (V) over a period of 2 months K. Martinez, J. K. Hart, R. Ong, IEEE Computer 37, (2004) Fluctuation of the battery level between 12.5 V and 14 V 10 W solar panel battery charge increases during summer 15

16 Example of an ESN: GLACSWEB system at Briksdalsbreen (Norway) Example: Base station temperature ( C) and tilt ( ), Sept. Dec temperature tilt K. Martinez, J. K. Hart, R. Ong, IEEE Computer 37, (2004) 16

17 Different Types of ESNs: ESNs vary in scale & function Examples: Large scale single function networks Localized multifunction sensor networks Biosensor networks (absolutely not comprehensive) J. K. Hart, K. Martinez, Earth-Science Reviews 78, (2006) 17

18 Large Scale Single-Function Networks: Cover large geographic areas Usually single equipped for purpose measurements Large and expensive nodes employed Examples: weather stations global seismographic network Most of the projects use simple star networks: central switch or hub numerous nodes star network: 18

19 Localized Multi-Function Networks: Comprise smaller nodes to monitor the environment Nodes normally measure generic properties like air temperature soil temperature humidity solar radiation etc. Localized multi-function networks measure straightforward environmental and meteorological properties example: water quality monitoring systems Wireless ad-hoc sensor networks providing cost-effective nodes simple installation 19

20 Biosensor Networks: Emerging sensor networks making use of biotechnology Biosensor networks generally require new sensor technology to test air, water and soil Requirements for biosensor networks: development of new instruments, especially sensors for in situ measurements of environmental proxies systems for continuous monitoring Biosensor networks are in their infancy Many test sensors have been already developed Ongoing research projects mainly address the problems of mobility, scale, sensing in water, development of new sensors 20

21 Heterogeneous Sensor Networks: Heterogeneous sensor networks include data sources from different types of ESN Monitoring of the environment at different scales Heterogeneous sensor networks are the envisioned future for ESN Rudimental example UK Climate Change Network ( long term integrated environmental monitoring & research program 12 terrestrial and 43 freshwater site in the UK are monitored most nodes measure a single function nodes could be linked together as an intelligent network in the future most parameters measured manually could be in principle also measured automatically 21

22 Challenges for ESNs: Challenges for ESNs (concerning data collection from sensor nodes in remote areas) power management miniaturization communication standardization remote management usability security data quality and error resiliency data management, mining, harvesting data analysis and visualization sensor technology 22

23 Power Management: ESN should work unattended maintenance-free (as long as possible) without continuous battery changes Low-power devices have to be deployed Intelligent power management has to be applied: essential for long-term operation strongly related to communications design (usually the dominant factor in power use) sophisticated power management techniques are essential 23

24 Miniaturization: ESNs often should be unobtrusive deployed in confined spaces Miniaturization is essential in many systems use surface mount components and double-sided boards use progammable logic instead of hardware solutions Limiting components: antenna size dielectric antennas, size of the order: l = λ / ε r, ε r 10 small size (e. g mm 3 ) good properties battery size radio power requirements

25 Communication: Radio communication success is unpredictable in wet and/or windy locations Theoretical calculations of radio losses are poorly related to reality examples: Useful: radio losses in glacier ice changes of leaf cover in forest habitats (especially in rain forests with high humidity) ability to alter transceiver power fall-back systems (acoustic, lower frequency) Communication between sensors nodes: useful if some nodes are out the range of the base station signals In any case: energy consumption has to be minimized!!! 25

26 Standardization: Today the compatibility between off-the-shelf modules is very low (e. g. between weather stations and dgps* units) Hardware platforms and operation software vary much interoperability is difficult In the future: it should be possible to deploy nodes from various vendors and analyze and visualize the data in a unified way interfaces and radio networking should be standardized interoperability between sensor networks of different vendors should be possible metadata and ontology standards should be defined allow for a global data information system * ) dgps: differential global positioning system 26

27 Remote Management: Systems in isolated areas can not be visited regularly remote access is essential bugs have to be fixed (automatically) subsystems might be shut down if necessary video control of the location can be useful power control to isolated subsystems is essential with regard to - power management - workarounds most careful software development and testing is very important intense failure scenario testing is required 27

28 Usability: Most ESN systems are developed as research platforms such systems require significant technical expertise for - general understanding - installation - maintenance - control -etc. In the future: simple interfaces are required plug-and-play style developments are necessary easy and effective data access is essential systems should be operable without technical expertise 28

29 Security: Security issues important at all levels of the ESN (physical measurements,, data interference) System should carry warnings, information and (if possible) alarms Systems should cope with loss (failure, damage, etc.) of one or several sensor nodes Data need to be protected against deliberate or accidental alteration Conventional network security protocols can be used (but: conventional protocols usually consume too much energy) Security systems should protect the ESN against tampering at the hardware level data level management level Security should NOT be used to hamper public access to information balance between security and information needs everybody should trust the systems 29

30 Data Quality and Error Resiliency: Enhancement of the data quality: sensor calibration is essential the exact source of the sensed data has to be defined information about the provenance of the setup is required information about the experimental circumstances are required define carefully how to extract and evaluate noisy/faulty data from systems composed of a large number of sensor nodes and etc. 30

31 Data Management, Mining, Harvesting: ESNs provide high-bandwidth, heterogeneous physical, chemical, and biological data streams Efficient data storage and management might be a challenge and has to be optimized Continued efforts on standardization and semantic markup can lead to an extremely high data availability Concerted efforts are required to make data mining simple for users software agents Metadata developments are required to promote data discovery, access, integration, and synthesis 31

32 Data Analysis and Visualization: Concerning the multidisciplinary analyses of data from ESNs it is necessary to define and develop appropriate tools for complex data analysis data visualization 32

33 Sensor Technology: Development of new sensors, e. g. biosensors sensor proxies envinodes The latest biosensors require further progress, for instance with regard to size cost reduction low-power design Computer systems used in nodes today are simple (to save power) higher integration into smaller packages ( system on a chip ) will improve the capabilities of nodes 33