AIT Chapter 5 Sensor Networks

1. Send signal with P_tx

2. Receive signal with P_recv with loss coefficient c

3. Estimate distance d P_recv = c* P_tx/d^a ↔ d = sqrt^a(cP_tx/P_recv)

Highly error-prone process

1. Receive signal measuring t_trans, v_prop and t_arrival

2. Compute distance d

1. Exact time synchronization required

2. Use round-trip time of signal // Two-way ToA

1. Send two signals with different v_prop // E.g. use ultrasound and radio

2. Receive signals measuring different t_arrival

3. Compute distance d

1. Expensive and energy-intensive HW required

2. Use global positioning system (GPS)

1. 32 satellites 20.000km above ground

2. Satellites broadcast ID and time reference

3. 4 broadcasts necessary for localization

4. For WSNs no GPS receivers but deploy nodes

1. Input with (x_i,y_i) coordinates of anchor point i, r_i distance to anchor i

2. Goal is to get (x_u,y_u) unknown coordinates of node

3. Solve system of equations via Pythagoras

1. (x_i-x_u)² + (y_i-y_u)² = r_i² for three nodes

2. Subtract third from first and second

3. Rearrange to linear equation for unknowns

2[x₃-x₁,y₃-y₁;x₃-x₂,y₃-y₂] * [x_u,y_u] = [(r₁²-r₃²)-(x₁²-x₃²)-(y₁²-y₃²);(r₂²-r₃²)-(x₂²-x₃²)-(y₂²-y₃²)]

1. If only r_i⁰ = r_i+eps_i available

2. Then use several anchors for over-determined system, minimizing mean square error

1. If nodes can not hear up to 3 anchors

2. Then spread position knowledge over simple nodes

3. But handle accumulated errors

Use angle for position estimates

1. On node

2. On special nodes

1. Mechanically rotate or 2. electrically steerable

1. Rotate at different offsets

2. Time between control frames yield angles

1. Factory floor automation

2. Disaster recovery // In an avalanche

3. Car-to-car communication finding empty parking lot

4. Military networking between tanks, soldiers

5. Personal area networking

1. Without infrastructure using networking abilities of participants

2. Network “for a special purpose”

3. Expensive equipment

4. “Human in the loop” applications

Self-organization

Multi-hopping

Adaptive protocols

Focus on interacting with the environment and not with humans

1. id-centric for MANET and 2. data-centric for WSN improving efficiency

1. Process information via sensing and actuation

2. Send answers instead of only numbers

3. Depends on application specifics

4. In-network event detection and processing

5. Combine WSNs with LIDAR, RADAR and web technologies

6. Must be fault-tolerant with a lifetime

7. Flexibility in form of programmability and maintainability

1. In case of wildfire to derive temperature map

2. Observe wildlife

3. Memory and energy constraint

4. Observe buildings for energy waste reduction or mechanical stress

5. Observe permafrost, glacier, landslide and trees

6. Facility management with intrusion and leakages

7. Machine surveillance and preventive maintenance

8. Precision agriculture

9. Medicine and health care

10. Logistics with equipping goods with sensor node

11. Telematics

12. Smart homes and cities

1. Behavior of wild rats in their natural habitat

2. Limited radio range therefor sporadic connectivity

1. Sensor-based landslide early warning system (SLEWS)

2. Volcano Deployment

3. Swiss experiment for micro-climate

1. Event detection and classification

2. Periodic measurement

3. Function approximation of space and or time

4. Edge detection in a function

5. Tracking of object

1. Core as WSN node

2. More additional equipment

IEEE 802.11n with higher data rates