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