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UbiCom Book Slides Chapter 6 Tagging, Sensing & Controlling Ubiquitous computing: smart devices,  environments  and intera...
Overview <ul><li>Introduction   </li></ul><ul><li>Tagging the Physical World </li></ul><ul><li>Sensors  and Sensor Networ...
Chapter 6: Overview <ul><li>The slides for this chapter are also expanded and split into several parts in the full pack </...
Overview <ul><li>Chapter 6 focuses on: </li></ul><ul><li>internal system properties: context-awareness & autonomy </li></u...
Introduction <ul><li>To enable Smart (Physical) Environments, devices should: </li></ul><ul><li>Spread more into the physi...
UbiCom Internal System Properties Ubiquitous computing: smart devices, environments and interaction
Smart Physical Environments Ubiquitous computing: smart devices, environments and interaction
Ubiquitous computing: smart devices, environments and interaction
Overview <ul><li>Introduction </li></ul><ul><li>Tagging the Physical World   </li></ul><ul><li>Sensors  and Sensor Networ...
Tagging (or Annotating) the Physical World <ul><li>Outline of this section </li></ul><ul><li>Applications </li></ul><ul><l...
Tagging: Applications <ul><li>Locate items, e.g.? </li></ul><ul><li>Retrieve annotations associated with physical objects ...
Tagging Applications: Automated Physical Access Ubiquitous computing: smart devices, environments and interaction
Tagging Applications: Asset Tracking Ubiquitous computing: smart devices, environments and interaction
Tagging Applications: Security Ubiquitous computing: smart devices, environments and interaction
Physical versus Virtual Tags Ubiquitous computing: smart devices, environments and interaction
Life-cycle for Tagging Physical Objects Ubiquitous computing: smart devices, environments and interaction
Design issues for Anchoring Tags on Physical Objects <ul><li>Different ways to characterise and classify tagging  </li></u...
Augment physical environments for use in virtual environments <ul><li>Augment the user:  </li></ul><ul><li>Augment the phy...
Onsite versus Offsite & Attached versus Detached Annotation  <ul><li>2 dimensions: </li></ul><ul><li>User of the annotatio...
Onsite versus Offsite & Attached versus Detached Annotation  Ubiquitous computing: smart devices, environments and interac...
Design issues for Anchoring Tags on Physical Objects Ubiquitous computing: smart devices, environments and interaction
Design issues for Tagging Physical environment <ul><li>Tags read outdoors in noisy, wet, dark or bright environments.  </l...
RFID Tags <ul><li>A type of on-site tag, attached to physical object </li></ul><ul><li>RFID (Radio Frequency Identifier) T...
RFID Tags: Applications <ul><li>???  </li></ul>Ubiquitous computing: smart devices, environments and interaction
Types of RFID Tag <ul><li>RFID tags may be classified into whether or not they: </li></ul><ul><ul><li>Active: </li></ul></...
Active RFID Tags <ul><li>Active RFID tags used on large, more expensive assets </li></ul><ul><li>.  </li></ul><ul><li>Typi...
Active RFID Transponders <ul><li>Active transponders are woken up when they receive a signal from a reader. </li></ul><ul>...
Active RFID Beacons <ul><li>Main difference c.f. Transponder is long range, global? beacon reader </li></ul><ul><li>Beacon...
Active RFID Transponder Application: toll booths Ubiquitous computing: smart devices, environments and interaction
Passive RFID Tags <ul><li>Contain no power source and no active transmitter </li></ul><ul><li>Power to transmit comes from...
Passive RFID Tags <ul><li>Passive tags typically operate at lower frequencies than active tags </li></ul><ul><li>Low-frequ...
Passive Tags: Near Field <ul><li>2.different approaches to transfer power from the reader to passive tags: near field and ...
Passive Tags: Far Field <ul><li>Why can’t electromagnetic induction be used? </li></ul><ul><li>So how does far field RFID ...
Business Use of Annotation <ul><li>Physical artefact annotation is often driven by business goals.  </li></ul><ul><li>Uniq...
Personal use of Annotation <ul><li>Tags are less specific, deterministic, multi-modal (using multiple sensory channels) us...
Personal use of Annotation: Semacode <ul><li>Semacode (2005) propose a scheme to define labels that can be automatically p...
Semacode Use Ubiquitous computing: smart devices, environments and interaction
Overview <ul><li>Introduction </li></ul><ul><li>Tagging the Physical World </li></ul><ul><li>Sensors  and Sensor Networks ...
Sensors: introduction <ul><li>Sensors are transducers that convert some physical phenomenon into an electrical signal </li...
Sensor Applications <ul><li>Give some examples of sensor use </li></ul><ul><li>Cars </li></ul><ul><li>Computers </li></ul>...
Sensors Types <ul><li>Sensors can be characterised according to: </li></ul><ul><li>Passive (tags) vs. active </li></ul><ul...
Sensors versus Tags <ul><li>??? </li></ul>Ubiquitous computing: smart devices, environments and interaction
Ubiquitous computing: smart devices, environments and interaction
Sensor Nets  <ul><li>Main components of a typical sensor network system are networked sensors nodes serviced by sensor acc...
Sensor Net: Functions <ul><li>The main functions of sensor networks can be layered in a protocol stack according to: </li>...
Sensor Net: Functions Ubiquitous computing: smart devices, environments and interaction
Sensors: Electronics
Sensor Net Design: Signal Detection & Processing <ul><li>Positioning & coverage of networks is important. Why? </li></ul>U...
Sensor Net Design: Positioning &  Coverage <ul><li>Given: sensor field (either known sensor locations, or spatial density)...
Sensor Net Design: Improved SNR Through Using Denser Sensor Nets <ul><li>Sensor has finite range determined by base-line (...
Overview <ul><li>Overview: Sensor Net Components & Processes </li></ul><ul><li>Physical Network: Environment, Density & Tr...
Senor Net Design: Sensor Data Routing <ul><li>Networking sensors versus networking computers? </li></ul><ul><li>Sensors fo...
Sensor Routing <ul><li>Make sensor address resolution efficient </li></ul><ul><li>Data centric routing,  </li></ul><ul><ul...
Sensor Networks vs. Ad Hoc Networks <ul><li>??? </li></ul>Ubiquitous computing: smart devices, environments and interaction
Sensor Net Topologies <ul><li>?? </li></ul>Ubiquitous computing: smart devices, environments and interaction
Senor Net Design: I n-Network Processing <ul><li>Why perform  I n-Network Processing?  </li></ul>Sensor  Node Sensors Ubiq...
Sensor Net: Data Storage & Retrieval <ul><li>What designs/ architectures can we use for sensor net data storage an retriev...
Sensor Database System <ul><li>Characteristics of a Sensor Network: </li></ul><ul><li>Can existing database techniques be ...
Sensor Net: Technologies, Kits & Standards <ul><li>Sun Spot: Java </li></ul><ul><li>Berkeley Motes: TinyOS, C </li></ul><u...
Overview <ul><li>Introduction </li></ul><ul><li>Tagging the Physical World </li></ul><ul><li>Sensors  and Sensor Networks ...
Micro Actuation and Sensing: MEMS <ul><li>Fabrication </li></ul><ul><li>Micro-Actuators </li></ul><ul><li>Micro-Sensors </...
Trend: Miniaturisation <ul><li>Electronic components become smaller, faster, cheaper to fabricate, lower power & lower mai...
Trend:     IC Transistor Density <ul><li>Gordon Moore (1965), Intel co-founder made a prediction, now popularly known as ...
MEMS: Introduction <ul><li>MEMS (Micro-electromechanical systems): micron- to millimetre-scale electronic devices fabricat...
MEMS Examples Electrostatic motor Actuator Hinge Gyroscope Ubiquitous computing: smart devices, environments and interaction
MEMS: Fabrication <ul><li>MEMS comprising mechanical and discrete electronic components </li></ul><ul><li>MEMS design is d...
MEMS: Fabrication <ul><li>Design a new circuit = design of interconnections among millions of relatively simple and identi...
MEMS : Fabrication <ul><li>Micromachines are fabricated just like ICs.  </li></ul><ul><li>MEMS type ICs can be fabricated ...
Micro-Actuator <ul><li>Mechanisms involved in micro-actuation whilst conceptually similar to equivalent macro mechanisms m...
Micro-actuator: Applications <ul><li>Micro-mirrors, e.g., ?? </li></ul><ul><li>Micro-fluid pumps, e.g., ?? </li></ul><ul><...
Micro-sensors <ul><li>Sensors are a type of transducer </li></ul><ul><li>Microsensors can work quite differently from equi...
MEMS: Applications <ul><li>Micro-accelerometers,  </li></ul><ul><ul><li>E.g., ?? </li></ul></ul><ul><li>Micro-gyroscopes  ...
Smart Device Form Factors: Smart Dust, Skins & Clay <ul><li>3 forms proposed by Weiser (1 tabs, 2 pads & 3 boards) can be ...
Smart Dust: MEMS <ul><li>MEMS can be sprayed into physical environment </li></ul><ul><li>E.g., Smart Dust project (Pister,...
Smart Skins: MEMS <ul><li>MEMS can be permanently attached to some fixed substrate forming  </li></ul><ul><ul><li>smart su...
Smart Clay: MEMS <ul><li>Claytronics project </li></ul><ul><li>Can behave as malleable  programmable matter   </li></ul><u...
MEMS: Challenges <ul><li>Establishing ownership of all of these micro items.  </li></ul><ul><li>Coping with data overload ...
Nanocomputing <ul><li>Nanocomputing can be defined as the manipulation, precision placement, measurement, modelling, and m...
Nanocomputing <ul><li>The drive to switch transistors faster and to be low-powered has been to make them smaller.  </li></...
Nanocomputing <ul><li>Nanotechnology at first proposed to use a bottom-up approach to design, to be able to assemble custo...
Overview <ul><li>Introduction </li></ul><ul><li>Tagging the Physical World </li></ul><ul><li>Sensors  and Sensor Networks ...
Embedded Systems: Introduction <ul><li>Is a component in a larger system  </li></ul><ul><li>Is programmable </li></ul><ul>...
Embedded System Characteristics  (Embedded vs. MTOS Systems) <ul><li>Traditionally, embedded systems differ from MTOS syst...
Embedded vs. MTOS Systems <ul><li>Often have constraints concerning  power consumption </li></ul><ul><li>Often are designe...
Embedded vs. MTOS Systems <ul><li>Each embedded computing devices may be designed for its own rigidly defined operational ...
Embedded Systems:  Hardware <ul><li>Microprocessors </li></ul><ul><li>Microcontroller </li></ul><ul><li>FPGA (Field Progra...
Real-Time System (RTS) <ul><li>Real-time systems (RTS) can be considered to be resource-constrained </li></ul><ul><li>Ofte...
RTS Design Concerns <ul><li>There are a range of real-time design concerns to support critical response time of a task: </...
RTS: Hard vs. Soft <ul><li>Timeliness is single most important aspect of RT system.  </li></ul><ul><li>RTS system is one w...
RTS: Soft <ul><li>Single computation arriving late may not be significant to the operation of the system,  </li></ul><ul><...
RTOS: Hard <ul><li>Timing requirements are vital.  </li></ul><ul><li>Response that’s late is incorrect and system failure ...
Safety-Critical Systems <ul><li>Instructors could add some text here or delete this slide. </li></ul>Ubiquitous computing:...
Overview <ul><li>Introduction </li></ul><ul><li>Tagging the Physical World </li></ul><ul><li>Sensors  and Sensor Networks ...
Links to other Topics <ul><li>Control systems / robots can be simple, operate in static deterministic environments. </li><...
Control Systems (For Physical World Tasks) <ul><li>Simply type of control  </li></ul><ul><ul><li>Activated only when defin...
Control Systems: Feedback Control <ul><li>2  basic kinds of feedback:  </li></ul><ul><ul><li>negative  </li></ul></ul><ul>...
Control Systems: Derivative (D) Feedback Control Ubiquitous computing: smart devices, environments and interaction
Control Systems: Proportional (P) Feedback Control <ul><li>In simple proportional (-ve feedback) control system </li></ul>...
Control Systems: PID Controllers <ul><li>Sometimes P type controller output is not regulated correctly </li></ul><ul><ul><...
Control Systems: PID Controllers <ul><li>Integral (I) controller deals with past behaviour of  control.  </li></ul><ul><li...
PID Controllers Ubiquitous computing: smart devices, environments and interaction
Programmable Controllers: Microcontrollers <ul><li>Hardware architecture of microcontrollers is much simpler than general ...
Complex Control Systems <ul><li>PID control  Useful for coarse-gained, static  control </li></ul><ul><ul><li>E.g., palleti...
Complex Control <ul><li>Several sources of uncertainty? </li></ul><ul><li>Techniques for controlling uncertain systems?  <...
Overview <ul><li>Introduction </li></ul><ul><li>Tagging the Physical World </li></ul><ul><li>Sensors  and Sensor Networks ...
Robots <ul><li>Early 1960s, robots started to be used to automate industrial tasks particularly in manufacturing </li></ul...
Main Robot Components <ul><li>Robots consist of:  </li></ul><ul><li>End effectors or actuators: </li></ul><ul><li>Locomoti...
Robots: Localisation <ul><li>Localisation is used to determine a robot’s position in relation to its physical environment....
Robots: Types <ul><li>3 Main Types </li></ul><ul><li>Robot manipulator or robot arm </li></ul><ul><li>Mobile robots </li><...
Robot Manipulators <ul><li>A manipulator consists of a linked chain of rigid bodies that are linked in an open kinematic c...
Robot Manipulators <ul><li>Also comprises 3 rotational DOF </li></ul><ul><ul><li>??? </li></ul></ul><ul><li>Joints are des...
Robot Manipulators: Design <ul><li>Motion planning needed </li></ul><ul><li>Control algorithms? </li></ul><ul><li>Regulati...
Mobile Robots <ul><li>Mobile robots use various kinds of locomotion systems </li></ul><ul><ul><li>? </li></ul></ul><ul><li...
Mobile Robots <ul><li>No.  of DOF  is often less compared to a robot manipulator.  </li></ul><ul><li>Need ways to navigate...
Biologically Inspired Robots: Legged locomotion  <ul><li>Biologically inspired robots  are more complex type of robot  </l...
Biologically Inspired Robots: Legged locomotion  <ul><li>The use of legs enables legged robots to travel over irregular te...
Biologically Inspired Robots: Human Robot Interaction <ul><li>Human robot Interaction: </li></ul><ul><ul><li>a specialisat...
Nanobots <ul><li>Nanobots  can be manufactured as MEMS or at molecular level.  </li></ul><ul><li>Microscopic world is gove...
Nanobots <ul><li>Nature in terms of micro-organisms can be harnessed in order to provide a host body for nanobots to move ...
Developing UbiCom Robot Applications <ul><li>Industrial types of robots </li></ul><ul><li>Low cost consumer type robots </...
Ultrasonic Sensor Light Sensor Motor A Motor B Motor C Ubiquitous computing: smart devices, environments and interaction
Developing UbiCom Robot Applications <ul><li>Task: robot manipulates a Rubik’s Cube to its solved state  </li></ul><ul><li...
Developing UbiCom Robot Applications <ul><li>Several practical issues for physical robots tasks execution </li></ul><ul><l...
Overview <ul><li>Introduction   </li></ul><ul><li>Tagging the Physical World   </li></ul><ul><li>Sensors  and Sensor Net...
Summary & Revision <ul><li>For each chapter </li></ul><ul><li>See book web-site for chapter summaries, references, resourc...
Exercises: Define New Concepts <ul><li>Annotation </li></ul>Ubiquitous computing: smart devices, environments and interact...
Exercise: Applying New Concepts Ubiquitous computing: smart devices, environments and interaction
Supplementary Slides <ul><li>Exercises & Solutions </li></ul>Ubiquitous computing: smart devices, environments and interac...
Sensor Applications <ul><li>Ex: Give some examples of sensor use </li></ul><ul><li>Cars: air pressure, brake-wear, car-doo...
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  1. 1. UbiCom Book Slides Chapter 6 Tagging, Sensing & Controlling Ubiquitous computing: smart devices, environments and interaction Stefan Poslad http://www.eecs.qmul.ac.uk/people/stefan/ubicom
  2. 2. Overview <ul><li>Introduction  </li></ul><ul><li>Tagging the Physical World </li></ul><ul><li>Sensors and Sensor Networks </li></ul><ul><li>Micro Sensing & MEMS </li></ul><ul><li>Micro Actuation & MEMS </li></ul><ul><li>Embedded Systems and Real-time Systems </li></ul><ul><li>Control Systems (For Physical World Tasks) </li></ul><ul><li>Robots </li></ul>Ubiquitous computing: smart devices, environments and interaction
  3. 3. Chapter 6: Overview <ul><li>The slides for this chapter are also expanded and split into several parts in the full pack </li></ul><ul><li>Part A: Tagging physical world & augmented reality </li></ul><ul><li>Part B: Sensors, Sensor Nets </li></ul><ul><li>Part C: MEMS </li></ul><ul><li>Part D: Embedded Systems </li></ul><ul><li>Part E: Control Systems & Robots </li></ul>Ubiquitous computing: smart devices, environments and interaction
  4. 4. Overview <ul><li>Chapter 6 focuses on: </li></ul><ul><li>internal system properties: context-awareness & autonomy </li></ul><ul><li>external interaction with the physical environment. </li></ul>Ubiquitous computing: smart devices, environments and interaction
  5. 5. Introduction <ul><li>To enable Smart (Physical) Environments, devices should: </li></ul><ul><li>Spread more into the physical environment, becoming part of more user activities in physical environment </li></ul><ul><li>Be cheap to operate: autonomous energy etc </li></ul><ul><li>Be low maintenance: automatic </li></ul><ul><li>Be able to interact with physical environment context </li></ul><ul><li>Be sometimes small enough so as to … </li></ul><ul><li>Be able to be encapsulated and embedded </li></ul><ul><li>Be cheap to manufacture </li></ul>Ubiquitous computing: smart devices, environments and interaction
  6. 6. UbiCom Internal System Properties Ubiquitous computing: smart devices, environments and interaction
  7. 7. Smart Physical Environments Ubiquitous computing: smart devices, environments and interaction
  8. 8. Ubiquitous computing: smart devices, environments and interaction
  9. 9. Overview <ul><li>Introduction </li></ul><ul><li>Tagging the Physical World  </li></ul><ul><li>Sensors and Sensor Networks </li></ul><ul><li>Micro Actuation and Sensing: MEMS </li></ul><ul><li>Embedded Systems and Real-time Systems </li></ul><ul><li>Control Systems (For Physical World Tasks) </li></ul><ul><li>Robots </li></ul>Ubiquitous computing: smart devices, environments and interaction
  10. 10. Tagging (or Annotating) the Physical World <ul><li>Outline of this section </li></ul><ul><li>Applications </li></ul><ul><li>Life-cycle for Tagging Physical Objects </li></ul><ul><li>Tags: Types and Characteristics </li></ul><ul><li>Physical and Virtual Tag Management </li></ul><ul><li>RFID Tags </li></ul><ul><li>Personalised and Social Tags </li></ul>Ubiquitous computing: smart devices, environments and interaction
  11. 11. Tagging: Applications <ul><li>Locate items, e.g.? </li></ul><ul><li>Retrieve annotations associated with physical objects (augmented reality) e.g. ? </li></ul><ul><li>Security, e/g/. . </li></ul><ul><li>Tracking, e.g., </li></ul><ul><li>Automated Routing: of physical objects, e.g., ? </li></ul><ul><li>Automated Physical Access: e.g., ? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  12. 12. Tagging Applications: Automated Physical Access Ubiquitous computing: smart devices, environments and interaction
  13. 13. Tagging Applications: Asset Tracking Ubiquitous computing: smart devices, environments and interaction
  14. 14. Tagging Applications: Security Ubiquitous computing: smart devices, environments and interaction
  15. 15. Physical versus Virtual Tags Ubiquitous computing: smart devices, environments and interaction
  16. 16. Life-cycle for Tagging Physical Objects Ubiquitous computing: smart devices, environments and interaction
  17. 17. Design issues for Anchoring Tags on Physical Objects <ul><li>Different ways to characterise and classify tagging </li></ul><ul><li>By how to augment physical world objects for use in virtual (computer) environments </li></ul><ul><li>By use of Onsite versus Offsite and attached versus detached classification of tags </li></ul>Ubiquitous computing: smart devices, environments and interaction
  18. 18. Augment physical environments for use in virtual environments <ul><li>Augment the user: </li></ul><ul><li>Augment the physical object: </li></ul><ul><li>Augment the surrounding environment: </li></ul>Ubiquitous computing: smart devices, environments and interaction
  19. 19. Onsite versus Offsite & Attached versus Detached Annotation <ul><li>2 dimensions: </li></ul><ul><li>User of the annotation is </li></ul><ul><ul><li>onsite (co-located or local) with physical object versus </li></ul></ul><ul><ul><li>offsite (not co-located or remote). </li></ul></ul><ul><li>Annotation is </li></ul><ul><ul><li>attached (or augments) physical object it refers to versus </li></ul></ul><ul><ul><li>being detached (not augmented or not collocated) with the physical object. </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  20. 20. Onsite versus Offsite & Attached versus Detached Annotation Ubiquitous computing: smart devices, environments and interaction Offsite Onsite Attached Detached
  21. 21. Design issues for Anchoring Tags on Physical Objects Ubiquitous computing: smart devices, environments and interaction
  22. 22. Design issues for Tagging Physical environment <ul><li>Tags read outdoors in noisy, wet, dark or bright environments. </li></ul><ul><li>Annotation data storage, distribution & integration with data </li></ul><ul><li>Data management must start as soon as the data is captured (readers). </li></ul><ul><li>Multiple tags & readers per unit Vol.. </li></ul><ul><ul><li>Challenges? </li></ul></ul><ul><li>Redundant annotations: similar items are captured, many times over. </li></ul><ul><ul><li>Solutions? </li></ul></ul><ul><li>Applications and businesses need to define the level of aggregation, reporting, analysis </li></ul>Ubiquitous computing: smart devices, environments and interaction
  23. 23. RFID Tags <ul><li>A type of on-site tag, attached to physical object </li></ul><ul><li>RFID (Radio Frequency Identifier) Tags, attached to objects to enable identification of objects in the world over a wireless link. </li></ul><ul><li>RFID Tags versus Bar codes? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  24. 24. RFID Tags: Applications <ul><li>??? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  25. 25. Types of RFID Tag <ul><li>RFID tags may be classified into whether or not they: </li></ul><ul><ul><li>Active: </li></ul></ul><ul><ul><li>Passive:. </li></ul></ul><ul><li>Active tags are more expensive and require more maintenance but have a longer range compared to passive tags. </li></ul><ul><li>Typical RFID system main components: </li></ul><ul><li>tag itself, reader, data storage, post-processing </li></ul><ul><li>RFID tag versus RF Smart Card? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  26. 26. Active RFID Tags <ul><li>Active RFID tags used on large, more expensive assets </li></ul><ul><li>. </li></ul><ul><li>Typically operate at 0.455, 2.45 or 5.8 GHz frequencies </li></ul><ul><li>Have a read range of 20 M to 100 M, </li></ul><ul><li>Cost? </li></ul><ul><li>Complex active tags could also incorporate sensors. How? Why? </li></ul><ul><li>2 types of active tags: transponders and beacons </li></ul>Ubiquitous computing: smart devices, environments and interaction
  27. 27. Active RFID Transponders <ul><li>Active transponders are woken up when they receive a signal from a reader. </li></ul><ul><li>Transponders conserve battery life. How? </li></ul><ul><li>Important application of active transponders is in toll payment collection, checkpoint control and other systems. </li></ul>Ubiquitous computing: smart devices, environments and interaction
  28. 28. Active RFID Beacons <ul><li>Main difference c.f. Transponder is long range, global? beacon reader </li></ul><ul><li>Beacons are used in Real-Time Location Systems (RTLS) </li></ul><ul><li>Longer range RTLS could utilise GPS or mobile phone GSM trilateration </li></ul><ul><ul><li>See Chapter 7 </li></ul></ul><ul><li>In RTLS, a beacon emits a signal with its unique identifier at pre-set intervals </li></ul>Ubiquitous computing: smart devices, environments and interaction
  29. 29. Active RFID Transponder Application: toll booths Ubiquitous computing: smart devices, environments and interaction
  30. 30. Passive RFID Tags <ul><li>Contain no power source and no active transmitter </li></ul><ul><li>Power to transmit comes from where? </li></ul><ul><li>Cheaper than active tags, cost? </li></ul><ul><li>Shorter (read access) range than active tags, typically ?? </li></ul><ul><li>Passive RFID transponder consists of a microchip attached to an antenna, e.g., same as smart card </li></ul><ul><li>Lower maintenance </li></ul><ul><li>Passive Transponders can be packaged in many different ways, </li></ul><ul><ul><li>???? </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  31. 31. Passive RFID Tags <ul><li>Passive tags typically operate at lower frequencies than active tags </li></ul><ul><li>Low-frequency tags are ideal for applications where the tag needs to be read through certain soft materials and water at a close range. Why? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  32. 32. Passive Tags: Near Field <ul><li>2.different approaches to transfer power from the reader to passive tags: near field and far field </li></ul><ul><li>Near field </li></ul><ul><li>Passive RFID interaction based upon electromagnetic induction. </li></ul><ul><li>Explain how this works here </li></ul>Ubiquitous computing: smart devices, environments and interaction
  33. 33. Passive Tags: Far Field <ul><li>Why can’t electromagnetic induction be used? </li></ul><ul><li>So how does far field RFID interaction work? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  34. 34. Business Use of Annotation <ul><li>Physical artefact annotation is often driven by business goals. </li></ul><ul><li>Uniquely identify objects from manufacture during business processes </li></ul>Ubiquitous computing: smart devices, environments and interaction
  35. 35. Personal use of Annotation <ul><li>Tags are less specific, deterministic, multi-modal (using multiple sensory channels) using multimedia. </li></ul><ul><li>Subjective annotations are used in multiple contexts, multiple applications and multiple activities by users. </li></ul><ul><li>Semantic gap challenge: between the low-level object features extracted and their high-level meaning with respect to a context of use </li></ul><ul><li>Several projects to tag personal views of physical world </li></ul><ul><ul><li>MyLifeBits </li></ul></ul><ul><ul><li>Semacode </li></ul></ul><ul><ul><li>Google Earth? But Is it personalised? </li></ul></ul><ul><ul><li>etc </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  36. 36. Personal use of Annotation: Semacode <ul><li>Semacode (2005) propose a scheme to define labels that can be automatically processed from captured images and linked to a Web-based spatial information encyclopaedia. </li></ul><ul><li>How does a semacode encodes URLs?? </li></ul><ul><li>How to create a semacodes? </li></ul><ul><li>How do read a Semacaode </li></ul><ul><li>Some management may be needed to control malicious removal, movement and attachment. </li></ul>Ubiquitous computing: smart devices, environments and interaction
  37. 37. Semacode Use Ubiquitous computing: smart devices, environments and interaction
  38. 38. Overview <ul><li>Introduction </li></ul><ul><li>Tagging the Physical World </li></ul><ul><li>Sensors and Sensor Networks  </li></ul><ul><li>Micro Actuation and Sensing: MEMS </li></ul><ul><li>Embedded Systems and Real-time Systems </li></ul><ul><li>Control Systems (For Physical World Tasks) </li></ul><ul><li>Robots </li></ul>Ubiquitous computing: smart devices, environments and interaction
  39. 39. Sensors: introduction <ul><li>Sensors are transducers that convert some physical phenomenon into an electrical signal </li></ul><ul><li>Wireless sensors: </li></ul><ul><li>Sensors can be networked – sensor nets </li></ul>Ubiquitous computing: smart devices, environments and interaction
  40. 40. Sensor Applications <ul><li>Give some examples of sensor use </li></ul><ul><li>Cars </li></ul><ul><li>Computers </li></ul><ul><li>Retail, logistics: </li></ul><ul><li>Household tasks </li></ul><ul><li>Buildings </li></ul><ul><li>Environment monitoring </li></ul><ul><li>Industrial sensing & diagnostics </li></ul>Ubiquitous computing: smart devices, environments and interaction
  41. 41. Sensors Types <ul><li>Sensors can be characterised according to: </li></ul><ul><li>Passive (tags) vs. active </li></ul><ul><li>Single sensors vs sensor arrays vs sensor nets </li></ul><ul><li>Read-only program vs. re-programmable </li></ul>Ubiquitous computing: smart devices, environments and interaction
  42. 42. Sensors versus Tags <ul><li>??? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  43. 43. Ubiquitous computing: smart devices, environments and interaction
  44. 44. Sensor Nets <ul><li>Main components of a typical sensor network system are networked sensors nodes serviced by sensor access node. </li></ul><ul><li>Slightly different but compatible view of a sensor network is to view sensors as being of three types of node): </li></ul><ul><ul><li>common nodes </li></ul></ul><ul><ul><li>sink nodes </li></ul></ul><ul><ul><li>gateway (access) </li></ul></ul><ul><li>In scenario given earlier, some sensors in the network can act as sink nodes within the network in addition to the access node. </li></ul><ul><li>Concepts of sensor node & sensor net can be ambiguous: </li></ul><ul><ul><li>A sensor can act as a node in a network of sensors versus there is a special sensor network server often called a sensor (access) node </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  45. 45. Sensor Net: Functions <ul><li>The main functions of sensor networks can be layered in a protocol stack according to: </li></ul><ul><ul><li>physical network characteristics, </li></ul></ul><ul><ul><li>data network characteristics </li></ul></ul><ul><ul><li>data processing and sensor choreography </li></ul></ul><ul><li>Use small network protocol stack for sensor nets. Why? </li></ul><ul><li>Other conceptual protocol layered stacks could also be used instead to model sensor operation, </li></ul>Ubiquitous computing: smart devices, environments and interaction
  46. 46. Sensor Net: Functions Ubiquitous computing: smart devices, environments and interaction
  47. 47. Sensors: Electronics
  48. 48. Sensor Net Design: Signal Detection & Processing <ul><li>Positioning & coverage of networks is important. Why? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  49. 49. Sensor Net Design: Positioning & Coverage <ul><li>Given: sensor field (either known sensor locations, or spatial density) </li></ul><ul><ul><li>Where to add new nodes for max coverage? </li></ul></ul><ul><ul><li>How to move existing nodes for max coverage? </li></ul></ul><ul><li>Can Control </li></ul><ul><ul><li>Area coverage: </li></ul></ul><ul><ul><li>Detectability: </li></ul></ul><ul><ul><li>Node coverage: </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  50. 50. Sensor Net Design: Improved SNR Through Using Denser Sensor Nets <ul><li>Sensor has finite range determined by base-line (floor) noise level </li></ul><ul><li>Denser sensor field improves detection of signal source within range. How? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  51. 51. Overview <ul><li>Overview: Sensor Net Components & Processes </li></ul><ul><li>Physical Network: Environment, Density & Transmission </li></ul><ul><li>Data Network: Addressing and Routing  </li></ul><ul><li>Data Processing: Distributed Data Storage & Data Queries </li></ul>Ubiquitous computing: smart devices, environments and interaction
  52. 52. Senor Net Design: Sensor Data Routing <ul><li>Networking sensors versus networking computers? </li></ul><ul><li>Sensors form P2P network with a mesh topology network </li></ul><ul><li>Sensors are massively distributed and work in real-time </li></ul><ul><li>No universal routing protocols or central registry. </li></ul><ul><li>Each node acts a router and application host. </li></ul>Ubiquitous computing: smart devices, environments and interaction
  53. 53. Sensor Routing <ul><li>Make sensor address resolution efficient </li></ul><ul><li>Data centric routing, </li></ul><ul><ul><li>Directed Diffusion </li></ul></ul><ul><ul><li>Flooding </li></ul></ul><ul><ul><li>Gossiping </li></ul></ul><ul><li>Routing classification </li></ul><ul><ul><li>Network structure: flat, hierarchical, hybrid </li></ul></ul><ul><ul><li>By interaction protocol </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  54. 54. Sensor Networks vs. Ad Hoc Networks <ul><li>??? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  55. 55. Sensor Net Topologies <ul><li>?? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  56. 56. Senor Net Design: I n-Network Processing <ul><li>Why perform I n-Network Processing? </li></ul>Sensor Node Sensors Ubiquitous computing: smart devices, environments and interaction
  57. 57. Sensor Net: Data Storage & Retrieval <ul><li>What designs/ architectures can we use for sensor net data storage an retrieval? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  58. 58. Sensor Database System <ul><li>Characteristics of a Sensor Network: </li></ul><ul><li>Can existing database techniques be reused? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  59. 59. Sensor Net: Technologies, Kits & Standards <ul><li>Sun Spot: Java </li></ul><ul><li>Berkeley Motes: TinyOS, C </li></ul><ul><li>SPINE (Signal Processing in Node Environment) </li></ul><ul><li>OGC Standards: SensorML etc </li></ul>Ubiquitous computing: smart devices, environments and interaction
  60. 60. Overview <ul><li>Introduction </li></ul><ul><li>Tagging the Physical World </li></ul><ul><li>Sensors and Sensor Networks </li></ul><ul><li>Micro Actuation and Sensing: MEMS  </li></ul><ul><li>Embedded Systems and Real-time Systems </li></ul><ul><li>Control Systems (For Physical World Tasks) </li></ul><ul><li>Robots </li></ul>Ubiquitous computing: smart devices, environments and interaction
  61. 61. Micro Actuation and Sensing: MEMS <ul><li>Fabrication </li></ul><ul><li>Micro-Actuators </li></ul><ul><li>Micro-Sensors </li></ul><ul><li>Smart Surfaces, Skin, Paint, Matter and Dust </li></ul><ul><li>Downsizing to Nanotechnology and Quantum Devices </li></ul>Ubiquitous computing: smart devices, environments and interaction
  62. 62. Trend: Miniaturisation <ul><li>Electronic components become smaller, faster, cheaper to fabricate, lower power & lower maintenance, they can be more easily deployed on a massive and pervasive scale. </li></ul><ul><li>MicroElectro Mechanical Systems ( MEMS ) are based upon IC Chip design </li></ul><ul><li>Possibilities for miniaturization extend into all aspects of life, & potential for embedding computing & comms technology quite literally everywhere is becoming a reality. </li></ul><ul><li>IT as an invisible component in everyone's surroundings </li></ul><ul><li>Extending the Internet deep into the physical environment </li></ul>Ubiquitous computing: smart devices, environments and interaction
  63. 63. Trend:  IC Transistor Density <ul><li>Gordon Moore (1965), Intel co-founder made a prediction, now popularly known as Moore's Law, which states that the number of transistors on an IC chip doubles ~ every 2 y </li></ul><ul><li>Does it mean that software processing capability will also increases in this way? </li></ul><ul><li> IC Chip density =  Software Performance? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  64. 64. MEMS: Introduction <ul><li>MEMS (Micro-electromechanical systems): micron- to millimetre-scale electronic devices fabricated as discrete devices or in large arrays </li></ul><ul><li>MEMS perform 2 basic types of functions: sensors or actuators. </li></ul><ul><li>Both act as transducers converting one signal into another. </li></ul><ul><li>MEMS actuators: electrical signal -> physical phenomena to move or control mechanisms. </li></ul><ul><li>MEMS Sensors work in reverse to actuators </li></ul>Ubiquitous computing: smart devices, environments and interaction
  65. 65. MEMS Examples Electrostatic motor Actuator Hinge Gyroscope Ubiquitous computing: smart devices, environments and interaction
  66. 66. MEMS: Fabrication <ul><li>MEMS comprising mechanical and discrete electronic components </li></ul><ul><li>MEMS design is different from macro devices </li></ul><ul><li>MEMS design are based upon IC chips design </li></ul><ul><li>Silicon based materials have: </li></ul><ul><ul><li>Well understood electrical properties </li></ul></ul><ul><ul><li>Good mechanical properties </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  67. 67. MEMS: Fabrication <ul><li>Design a new circuit = design of interconnections among millions of relatively simple and identical components. </li></ul><ul><li>Diversity and complexity of the interconnections -> diversity of electronic components including memory chips and CPUs. </li></ul><ul><li>Multiplicity, batch fabrication, is inherent. </li></ul><ul><li>Miniaturisation of IC based MEMS processing has important advantages over macro electromechanical devices and systems? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  68. 68. MEMS : Fabrication <ul><li>Micromachines are fabricated just like ICs. </li></ul><ul><li>MEMS type ICs can be fabricated in different ways using: </li></ul><ul><ul><li>Bulk micro-machining </li></ul></ul><ul><ul><li>Surface micro-machining </li></ul></ul><ul><ul><li>LIGA deep structures. </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  69. 69. Micro-Actuator <ul><li>Mechanisms involved in micro-actuation whilst conceptually similar to equivalent macro mechanisms may function fundamentally differently, </li></ul><ul><li>Are engineered in a fundamentally different way using IC </li></ul>Ubiquitous computing: smart devices, environments and interaction
  70. 70. Micro-actuator: Applications <ul><li>Micro-mirrors, e.g., ?? </li></ul><ul><li>Micro-fluid pumps, e.g., ?? </li></ul><ul><li>Miniature RF transceivers, e.g., ?? </li></ul><ul><li>Miniature Storage devices, e.g., ?? </li></ul><ul><li>Etc </li></ul>Ubiquitous computing: smart devices, environments and interaction
  71. 71. Micro-sensors <ul><li>Sensors are a type of transducer </li></ul><ul><li>Microsensors can work quite differently from equivalent macro sensor, </li></ul><ul><li>Sensors enable adaptation </li></ul><ul><li>Often embedded into system as part of a control loop </li></ul>Ubiquitous computing: smart devices, environments and interaction
  72. 72. MEMS: Applications <ul><li>Micro-accelerometers, </li></ul><ul><ul><li>E.g., ?? </li></ul></ul><ul><li>Micro-gyroscopes </li></ul><ul><ul><li>E.g., </li></ul></ul><ul><li>Detecting Structural Changes </li></ul><ul><ul><li>E.g., </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  73. 73. Smart Device Form Factors: Smart Dust, Skins & Clay <ul><li>3 forms proposed by Weiser (1 tabs, 2 pads & 3 boards) can be extended to include 3 more forms: </li></ul><ul><li>Smart Dust : </li></ul><ul><li>Smart Skins : </li></ul><ul><li>Smart Clay : </li></ul>Ubiquitous computing: smart devices, environments and interaction
  74. 74. Smart Dust: MEMS <ul><li>MEMS can be sprayed into physical environment </li></ul><ul><li>E.g., Smart Dust project (Pister, UC,Berkely) </li></ul><ul><li>(see Chapter 2) </li></ul>Ubiquitous computing: smart devices, environments and interaction
  75. 75. Smart Skins: MEMS <ul><li>MEMS can be permanently attached to some fixed substrate forming </li></ul><ul><ul><li>smart surfaces </li></ul></ul><ul><ul><li>smart skin </li></ul></ul><ul><li>E.g. Paint that is able to sense vibrations </li></ul><ul><li>See also Organic Displays (Chapter 5) </li></ul>Ubiquitous computing: smart devices, environments and interaction
  76. 76. Smart Clay: MEMS <ul><li>Claytronics project </li></ul><ul><li>Can behave as malleable programmable matter </li></ul><ul><li>Are MEMS ensembles </li></ul><ul><li>Self-assembled into any arbitrary 3D shape </li></ul><ul><li>Goal to achieve a synthetic reality. </li></ul>Ubiquitous computing: smart devices, environments and interaction
  77. 77. MEMS: Challenges <ul><li>Establishing ownership of all of these micro items. </li></ul><ul><li>Coping with data overload </li></ul><ul><li>Different Low-level patterns of signals may be ambiguous and variable. </li></ul><ul><li>Handling context switches between these augmented environment events via assisted senses and the unassisted ones. </li></ul><ul><li>Are micro-devices either easy to dispose of or hard to dispose of? </li></ul><ul><ul><li>What is we swallow / breath them in? </li></ul></ul><ul><li>How to manage MEMS? </li></ul><ul><ul><li>See Chapter 12 </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  78. 78. Nanocomputing <ul><li>Nanocomputing can be defined as the manipulation, precision placement, measurement, modelling, and manufacture to create systems with less than 100 nm </li></ul><ul><li>Also referred to as nanotechnology </li></ul><ul><li>Is based upon a broader range of materials, mechanisms & sizes down to molecular level </li></ul><ul><li>MEMS Vs. Nanocomputing? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  79. 79. Nanocomputing <ul><li>The drive to switch transistors faster and to be low-powered has been to make them smaller. </li></ul><ul><li>When electronic components approach nanometer sizes, odd things begin to happen. What? </li></ul><ul><li>This raised an early concern about the feasibility of nanotechnology. </li></ul><ul><li>Other challenges are: </li></ul><ul><li>thermal noise </li></ul><ul><li>positioning and the control of structures at this level </li></ul>Ubiquitous computing: smart devices, environments and interaction
  80. 80. Nanocomputing <ul><li>Nanotechnology at first proposed to use a bottom-up approach to design, to be able to assemble custom-made molecular structures for specific applications, </li></ul><ul><li>A major challenge to this design process is the complexity and novelty in understanding and being able to model materials at this level. </li></ul><ul><li>More research is needed to understand how combinations of materials, in particular compounds, gives materials at the molecular level certain physical and functional properties.. </li></ul>Ubiquitous computing: smart devices, environments and interaction
  81. 81. Overview <ul><li>Introduction </li></ul><ul><li>Tagging the Physical World </li></ul><ul><li>Sensors and Sensor Networks </li></ul><ul><li>Micro Actuation and Sensing: MEMS </li></ul><ul><li>Embedded Systems and Real-time Systems  </li></ul><ul><li>Control Systems (For Physical World Tasks) </li></ul><ul><li>Robots </li></ul>Ubiquitous computing: smart devices, environments and interaction
  82. 82. Embedded Systems: Introduction <ul><li>Is a component in a larger system </li></ul><ul><li>Is programmable </li></ul><ul><li>Performs a single, dedicated task. </li></ul><ul><li>May or may not be visible as a computer to a user of that system </li></ul><ul><li>May or may not have a visible control interface </li></ul><ul><li>E.g., ??? </li></ul><ul><li>May be local or remote, </li></ul><ul><ul><li>e.g., ?? </li></ul></ul><ul><li>fixed or mobile </li></ul><ul><ul><li>e.g?? </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  83. 83. Embedded System Characteristics (Embedded vs. MTOS Systems) <ul><li>Traditionally, embedded systems differ from MTOS systems </li></ul><ul><li>OS of Embedded systems differ vs. MTOS system </li></ul><ul><li>Specialised to single task enactment (ASOS) </li></ul><ul><li>Actions on physical world tasks are often scheduled with respect to real-time constraints (RTOS) </li></ul><ul><li>Safety-criticality is considered more important </li></ul>Ubiquitous computing: smart devices, environments and interaction
  84. 84. Embedded vs. MTOS Systems <ul><li>Often have constraints concerning power consumption </li></ul><ul><li>Often are designed to operate over a wide-range of physical environmental conditions compared to PC </li></ul><ul><ul><li>e.g., </li></ul></ul><ul><li>Often operate under moderate to severe real-time constraints. </li></ul><ul><li>System failures can have life-threatening consequences. </li></ul><ul><ul><li>E.g., </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  85. 85. Embedded vs. MTOS Systems <ul><li>Each embedded computing devices may be designed for its own rigidly defined operational bounds </li></ul><ul><ul><li>e.g., </li></ul></ul><ul><li>Linking embedded systems to external systems </li></ul><ul><li>Designs often engineered for a trade-off </li></ul><ul><li>Fewer system resources then PC. How? </li></ul><ul><li>Embedded systems not always easy to programme. Why? </li></ul><ul><li>Most embedded designs (hardware & software) are unique </li></ul><ul><li>Use a far simpler & cheaper OS & hardware. Why? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  86. 86. Embedded Systems: Hardware <ul><li>Microprocessors </li></ul><ul><li>Microcontroller </li></ul><ul><li>FPGA (Field Programmable Gate Arrays): </li></ul>Ubiquitous computing: smart devices, environments and interaction
  87. 87. Real-Time System (RTS) <ul><li>Real-time systems (RTS) can be considered to be resource-constrained </li></ul><ul><li>Often RTS perform safety-critical tasks </li></ul><ul><li>RTS reacts to external events that interrupt it: </li></ul><ul><li>RTS uses mechanisms for priority scheduling of interrupts </li></ul><ul><li>RTOS may also use additional process control: </li></ul><ul><ul><li>. </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  88. 88. RTS Design Concerns <ul><li>There are a range of real-time design concerns to support critical response time of a task: </li></ul><ul><li>Need to optimise </li></ul><ul><ul><li>both response time and data transfer rate </li></ul></ul><ul><ul><li>optimising these when there are simultaneous tasks. </li></ul></ul><ul><li>Key factors that affect the response time are? </li></ul><ul><ul><li>process context-switching </li></ul></ul><ul><ul><li>interrupt latency </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  89. 89. RTS: Hard vs. Soft <ul><li>Timeliness is single most important aspect of RT system. </li></ul><ul><li>RTS system is one where timing of result is just as important as the result itself. </li></ul><ul><li>A correct answer produced too late is just as bad as an incorrect answer or no answer at all. </li></ul><ul><li>RTS correctness of computations not only depends upon the logical correctness of the computation but also upon time to produce results. </li></ul><ul><li>If the timing constraints are not met, system failure occurs </li></ul><ul><li>Timing constraints can vary between different real-time systems. </li></ul><ul><li>Therefore, RTS can fall into one of three categories: soft, hard or firm.. </li></ul>Ubiquitous computing: smart devices, environments and interaction
  90. 90. RTS: Soft <ul><li>Single computation arriving late may not be significant to the operation of the system, </li></ul><ul><ul><li>Although many late arrivals might be significant </li></ul></ul><ul><li>Timing requirements can be defined by using an average response time. </li></ul>Ubiquitous computing: smart devices, environments and interaction
  91. 91. RTOS: Hard <ul><li>Timing requirements are vital. </li></ul><ul><li>Response that’s late is incorrect and system failure results. </li></ul><ul><li>Activities must complete by specified deadline, always. </li></ul><ul><li>Different types of deadlines. What? </li></ul><ul><li>If a deadline is missed the task fails </li></ul><ul><ul><li>E.g., ?? </li></ul></ul><ul><li>This demands that the system has the ability to predict how long computations will take in advance. </li></ul>Ubiquitous computing: smart devices, environments and interaction
  92. 92. Safety-Critical Systems <ul><li>Instructors could add some text here or delete this slide. </li></ul>Ubiquitous computing: smart devices, environments and interaction
  93. 93. Overview <ul><li>Introduction </li></ul><ul><li>Tagging the Physical World </li></ul><ul><li>Sensors and Sensor Networks </li></ul><ul><li>Micro Actuation and Sensing: MEMS </li></ul><ul><li>Embedded Systems and Real-time Systems </li></ul><ul><li>Control Systems (For Physical World Tasks)  </li></ul><ul><li>Robots </li></ul>Ubiquitous computing: smart devices, environments and interaction
  94. 94. Links to other Topics <ul><li>Control systems / robots can be simple, operate in static deterministic environments. </li></ul><ul><li>To operate in more dynamic non- deterministic environments, they can make use of AI techniques (Chapters 8-10). </li></ul><ul><li>HCI aspects of (biologically inspired) robots such as affective computing etc (Chapter 5) </li></ul>Ubiquitous computing: smart devices, environments and interaction
  95. 95. Control Systems (For Physical World Tasks) <ul><li>Simply type of control </li></ul><ul><ul><li>Activated only when defined thresholds are crossed, </li></ul></ul><ul><ul><li>e.g., . </li></ul></ul><ul><li>Disadvantages? </li></ul><ul><li>Solutions? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  96. 96. Control Systems: Feedback Control <ul><li>2 basic kinds of feedback: </li></ul><ul><ul><li>negative </li></ul></ul><ul><ul><li>positive </li></ul></ul><ul><li>Negative feedback </li></ul><ul><li>Seeks to reduce some change in a system output or state </li></ul><ul><li>Based upon derivative of output </li></ul><ul><li>Which is then used to modify input to regulate output. </li></ul><ul><li>Several types of feedback control: D, P, I, PID </li></ul><ul><li>Positive feedback </li></ul><ul><li>Acts to amplify a system state or output </li></ul>Ubiquitous computing: smart devices, environments and interaction
  97. 97. Control Systems: Derivative (D) Feedback Control Ubiquitous computing: smart devices, environments and interaction
  98. 98. Control Systems: Proportional (P) Feedback Control <ul><li>In simple proportional (-ve feedback) control system </li></ul><ul><li>Action taken to negatively feedback a signal to the plant, </li></ul><ul><li>Is in proportion to the degree the system diverges from the reference value </li></ul><ul><li>This leads to a much smoother regulation </li></ul><ul><ul><li>e.g.,. </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  99. 99. Control Systems: PID Controllers <ul><li>Sometimes P type controller output is not regulated correctly </li></ul><ul><ul><li>e.g., ?? </li></ul></ul><ul><li>To solve this problem either integral or differential control or both can be added to the control. </li></ul><ul><li>PID controller is so named because it combines Proportional, Integral and Derivative type control </li></ul><ul><li>Proportional (P) controller is just the error signal multiplied by a constant and fed out to a hardware drive. </li></ul>Ubiquitous computing: smart devices, environments and interaction
  100. 100. Control Systems: PID Controllers <ul><li>Integral (I) controller deals with past behaviour of control. </li></ul><ul><li>Derivative (D) type controller is used to predict the plant behaviour </li></ul><ul><li>P, PI, PD or PID control are often simple enough, to be hard-coded into controllers </li></ul><ul><li>Usually support some adjustment controls, </li></ul><ul><ul><li>e.g., </li></ul></ul><ul><li>PID controllers can be designed to be programmable </li></ul>Ubiquitous computing: smart devices, environments and interaction
  101. 101. PID Controllers Ubiquitous computing: smart devices, environments and interaction
  102. 102. Programmable Controllers: Microcontrollers <ul><li>Hardware architecture of microcontrollers is much simpler than general purpose processor mother-boards in PCs? </li></ul><ul><li>I/O control support can be simpler as there may not be any video screen output or keyboard input. </li></ul><ul><li>Micro-controllers can range in complexity </li></ul><ul><li>Originally, programmed in assembly language, later in C </li></ul><ul><li>Control programs often developed in an emulator on a PC </li></ul><ul><li>More recent microcontrollers can be integrated with on-chip debug circuitry accessed by an in-circuit emulator </li></ul>Ubiquitous computing: smart devices, environments and interaction
  103. 103. Complex Control Systems <ul><li>PID control Useful for coarse-gained, static control </li></ul><ul><ul><li>E.g., palletising, coarse-controlled locomotion, etc </li></ul></ul><ul><li>PID control not suitable for ? </li></ul><ul><ul><li>fine-grained </li></ul></ul><ul><ul><li>dynamic control </li></ul></ul><ul><ul><li>uncertainties in control </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  104. 104. Complex Control <ul><li>Several sources of uncertainty? </li></ul><ul><li>Techniques for controlling uncertain systems? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  105. 105. Overview <ul><li>Introduction </li></ul><ul><li>Tagging the Physical World </li></ul><ul><li>Sensors and Sensor Networks </li></ul><ul><li>Micro Actuation and Sensing: MEMS </li></ul><ul><li>Embedded Systems and Real-time Systems </li></ul><ul><li>Control Systems (For Physical World Tasks) </li></ul><ul><li>Robots  </li></ul>Ubiquitous computing: smart devices, environments and interaction
  106. 106. Robots <ul><li>Early 1960s, robots started to be used to automate industrial tasks particularly in manufacturing </li></ul><ul><li>Why Automate? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  107. 107. Main Robot Components <ul><li>Robots consist of: </li></ul><ul><li>End effectors or actuators: </li></ul><ul><li>Locomotion: </li></ul><ul><li>Drive: </li></ul><ul><li>Controller </li></ul><ul><li>Sensor </li></ul>Ubiquitous computing: smart devices, environments and interaction
  108. 108. Robots: Localisation <ul><li>Localisation is used to determine a robot’s position in relation to its physical environment. </li></ul><ul><li>Localisation can be local or global. </li></ul><ul><li>Local localisation is often simpler in which a robot corrects its position in relation to its initial or other current reference location. </li></ul><ul><li>Global localisation is discussed more in context-aware systems part. </li></ul>Ubiquitous computing: smart devices, environments and interaction
  109. 109. Robots: Types <ul><li>3 Main Types </li></ul><ul><li>Robot manipulator or robot arm </li></ul><ul><li>Mobile robots </li></ul><ul><li>Biologically inspired robots </li></ul>Ubiquitous computing: smart devices, environments and interaction
  110. 110. Robot Manipulators <ul><li>A manipulator consists of a linked chain of rigid bodies that are linked in an open kinematic chain at joints. </li></ul><ul><li>rigid body can have up to 6 Degrees Of Freedom (DOF) of movement. </li></ul><ul><li>This comprises 3 translational DOF </li></ul><ul><ul><li>??? </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  111. 111. Robot Manipulators <ul><li>Also comprises 3 rotational DOF </li></ul><ul><ul><li>??? </li></ul></ul><ul><li>Joints are designed to restrict some DOF. </li></ul><ul><li>Human operators may be in the control loop of robot manipulators. Why? </li></ul>Ubiquitous computing: smart devices, environments and interaction
  112. 112. Robot Manipulators: Design <ul><li>Motion planning needed </li></ul><ul><li>Control algorithms? </li></ul><ul><li>Regulation of contact force </li></ul><ul><li>Manipulators need to cope with variations in components and objects being manipulated. Solutions? </li></ul><ul><ul><li>Use adaptive AI techniques (Chapter 8) </li></ul></ul><ul><ul><li>Put human in the control loop </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  113. 113. Mobile Robots <ul><li>Mobile robots use various kinds of locomotion systems </li></ul><ul><ul><li>? </li></ul></ul><ul><li>Simplest types of mobile robots to control </li></ul><ul><ul><li>?? </li></ul></ul><ul><li>In dynamic non-deterministic environments, control is more complicated </li></ul><ul><li>A more complex, well-known & highly successful use of mobile robots was Mars Explorer Robots </li></ul>Ubiquitous computing: smart devices, environments and interaction
  114. 114. Mobile Robots <ul><li>No. of DOF is often less compared to a robot manipulator. </li></ul><ul><li>Need ways to navigate obstacles? </li></ul><ul><li>Simple approach: use collision detection </li></ul><ul><li>More complex approach: anticipate & avoid collisions </li></ul><ul><ul><li>Need environment models (AI, Chapter 8) </li></ul></ul><ul><ul><li>Need to replan paths to reach goal destinations (AI, Chapter 8) </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  115. 115. Biologically Inspired Robots: Legged locomotion <ul><li>Biologically inspired robots are more complex type of robot </li></ul><ul><ul><li>Combines legged locomotion capabilities & manipulator </li></ul></ul><ul><li>2 main focuses to these robots: </li></ul><ul><ul><li>Legged locomotion (in combination with manipulator) </li></ul></ul><ul><ul><li>Human-Robot Interaction </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  116. 116. Biologically Inspired Robots: Legged locomotion <ul><li>The use of legs enables legged robots to travel over irregular terrain </li></ul><ul><li>Biped robots often have more DOF than either the mobile robot or robot manipulator </li></ul><ul><li>Particular design challenge for biped robots is stability </li></ul>Ubiquitous computing: smart devices, environments and interaction
  117. 117. Biologically Inspired Robots: Human Robot Interaction <ul><li>Human robot Interaction: </li></ul><ul><ul><li>a specialisation of HCI, see Chapter 5 </li></ul></ul><ul><li>Robots can assist humans and extend sensing capabilities of (less able?) humans – Posthuman model. </li></ul><ul><li>Robots can fulfil social roles </li></ul><ul><ul><li>i.e., affective computing (Chapter 5) </li></ul></ul><ul><ul><li>e.g., artificial pets </li></ul></ul><ul><li>Social guided learning </li></ul><ul><ul><li>Learning by imitation or by tutelage </li></ul></ul><ul><li>Use of more human oriented interface & interaction </li></ul><ul><ul><li>E.g., speech recognition </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  118. 118. Nanobots <ul><li>Nanobots can be manufactured as MEMS or at molecular level. </li></ul><ul><li>Microscopic world is governed by the same physical laws as the macroscopic world </li></ul><ul><li>But relative importance of the physical laws change in how it affects the mechanics and the electronics at this scale </li></ul>Ubiquitous computing: smart devices, environments and interaction
  119. 119. Nanobots <ul><li>Nature in terms of micro-organisms can be harnessed in order to provide a host body for nanobots to move about </li></ul><ul><ul><li>e.g., </li></ul></ul><ul><li>Shrinking device size to these nano dimensions leads to many interesting challenges: </li></ul>Ubiquitous computing: smart devices, environments and interaction
  120. 120. Developing UbiCom Robot Applications <ul><li>Industrial types of robots </li></ul><ul><li>Low cost consumer type robots </li></ul><ul><li>Robots toolkits that are programmable. </li></ul>Ubiquitous computing: smart devices, environments and interaction
  121. 121. Ultrasonic Sensor Light Sensor Motor A Motor B Motor C Ubiquitous computing: smart devices, environments and interaction
  122. 122. Developing UbiCom Robot Applications <ul><li>Task: robot manipulates a Rubik’s Cube to its solved state </li></ul><ul><li>Goal: robot performs whole task or guides humans to do it </li></ul><ul><li>Design involves </li></ul><ul><li>Design: of the robot mechanics </li></ul><ul><li>Design: how and when the robot senses state of the world </li></ul><ul><ul><li>e.g. , </li></ul></ul><ul><li>Planning algorithm: to link individual actions </li></ul><ul><li>Overall architecture: to integrate different sub-tasks </li></ul><ul><ul><li>e.g., </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
  123. 123. Developing UbiCom Robot Applications <ul><li>Several practical issues for physical robots tasks execution </li></ul><ul><li>Sensor accuracy </li></ul><ul><li>Position accuracy </li></ul><ul><li>Variable amounts of friction during movement </li></ul><ul><li>Some elasticity in the robot arm </li></ul><ul><li>Low-level design to tell robots to carry out specific tasks </li></ul><ul><li>Tasks need to be designed to fit the robots capabilities </li></ul><ul><li>In open physical world, much non-determinism to handle </li></ul><ul><li>-> There does not yet exist, flexible general purpose UbiCom robots, which can act as autonomous assistants or servants for mass human use. </li></ul>Ubiquitous computing: smart devices, environments and interaction
  124. 124. Overview <ul><li>Introduction  </li></ul><ul><li>Tagging the Physical World  </li></ul><ul><li>Sensors and Sensor Networks  </li></ul><ul><li>Micro Actuation and Sensing: MEMS  </li></ul><ul><li>Embedded Systems and Real-time Systems  </li></ul><ul><li>Control Systems (For Physical World Tasks)  </li></ul><ul><li>Robots  </li></ul>Ubiquitous computing: smart devices, environments and interaction
  125. 125. Summary & Revision <ul><li>For each chapter </li></ul><ul><li>See book web-site for chapter summaries, references, resources etc. </li></ul><ul><li>Identify new terms & concepts </li></ul><ul><li>Apply new terms and concepts: define, use in old and new situations & problems </li></ul><ul><li>Debate problems, challenges and solutions </li></ul><ul><li>See Chapter exercises on web-site </li></ul>Ubiquitous computing: smart devices, environments and interaction
  126. 126. Exercises: Define New Concepts <ul><li>Annotation </li></ul>Ubiquitous computing: smart devices, environments and interaction
  127. 127. Exercise: Applying New Concepts Ubiquitous computing: smart devices, environments and interaction
  128. 128. Supplementary Slides <ul><li>Exercises & Solutions </li></ul>Ubiquitous computing: smart devices, environments and interaction
  129. 129. Sensor Applications <ul><li>Ex: Give some examples of sensor use </li></ul><ul><li>Cars: air pressure, brake-wear, car-doors, engine etc </li></ul><ul><li>Lap-top: accelerometers – switch off computer disks when dropped </li></ul><ul><li>Retail, logistics: RFIDs </li></ul><ul><li>Heaters: thermostats </li></ul><ul><li>Infrastructure protection / Intrusion detection (active sensors) </li></ul><ul><li>Environment monitoring </li></ul><ul><li>Industrial sensing & diagnostics </li></ul><ul><li>Battlefield awareness </li></ul><ul><li>Sensors can be characterised according to: </li></ul><ul><ul><li>passive (tags) vs. active </li></ul></ul><ul><ul><li>Single sensors vs sensor arrays vs sensor nets </li></ul></ul><ul><ul><li>Read-only program vs. re-programmable </li></ul></ul>Ubiquitous computing: smart devices, environments and interaction
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