environmental monitoring: from sensors to database

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ENVIRONMENTAL MONITORING: FROM SENSORS TO DATABASE Jerry Yang

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Environmental monitoring: from sensors to database. Jerry Yang. Overview. Design Requirement System Framework Wireless Sensor Networks Communications Protocols Data Interpolating Energy Harvesting Over-the-Air Programming Telecommunication system Single Board Computer GPRS modem - PowerPoint PPT Presentation

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Page 1: Environmental monitoring: from sensors to database

ENVIRONMENTAL MONITORING:FROM SENSORS TO DATABASEJerry Yang

Page 2: Environmental monitoring: from sensors to database

Overview Design Requirement System Framework

Wireless Sensor Networks Communications Protocols Data Interpolating Energy Harvesting Over-the-Air Programming

Telecommunication system Single Board Computer GPRS modem Networking sensors, data loggers and data servers

Database and Client Interfaces Database Data Visualization

Conclusion and Future Work

Page 3: Environmental monitoring: from sensors to database

Project Object Design and implement a fully functional

environmental monitoring system Collect and report temporal and spatial soil

moisture data with required accuracy Provide near-real-time data about monitored

variables to the public Monolithic weather stations

Wired Sensors (Data loggers) limited Spatial Coverage

Field Study Data is acquired every month

Page 4: Environmental monitoring: from sensors to database

Go Wireless Wireless Sensors could fulfill this mission

Unprecedented temporal and spatial granularities

Near-real-time data is accessible via the Internet

Besides… Robust and accurate through dense

deployment Minimize disturbance to the monitored site Cover larger area (Multihop) Low installation cost Ease of deployment and relocation

Page 5: Environmental monitoring: from sensors to database

System Architecture

Database Server

Internet

Client Data Browsingand Processing

Data loggers

In the Field:Download Data

In the Lab:Upload Data

Page 6: Environmental monitoring: from sensors to database

System Architecture

Database Server

Internet

Client Data Browsingand Processing

Base Station Node

Wireless Sensor Nodes

GPRS Modem

Gateway (Single Board Computer)

GPRS Link

Data loggers

Page 7: Environmental monitoring: from sensors to database

An introduction to WSNs A wireless sensor mote is a battery-operated

embedded system including various hardware and software components. For MicaZ motes: Processing Unit

7.37MHz micro-controller 4KB RAM 512KB Flash

Sensors 16-bit ADC with MDA 300 Data Acquisition Board EC-5 Soil Moisture Sensors

Transceiver 2.4 GHz, IEEE 802.15.4 compliant, 250 kbps

Powered by 2 AA batteries

Page 8: Environmental monitoring: from sensors to database

Constraints of Sensor Motes Limited processing, storage and communication

capabilities 100 nodes @250bps = 25kbps (data sampled every second) WILL be solved in the near future

year

Streaming Data to/from the Physical

World

Page 9: Environmental monitoring: from sensors to database

Fundamental Problem Sensor network is un-tethered, and will be

operating for a long time. Replacing batteries is difficult and expensive if not

impossible For MicaZ, typical current drawing is 30mA. Powered by

2.4V 3000mAh Batteries, a MicaZ mote could run for 100 hours continuously.

Communicating 1 bit data over the wireless medium consumes far more energy than processing it.

Operating Current (mA) MicaZ ATMega128L, full operation 12 (7.37 MHz)

ATMega128L, sleep 0.010 Radio, receive 19.7

Radio, transmit (0dBm) 17 Radio, sleep 0.001

Page 10: Environmental monitoring: from sensors to database

Software Support TinyOS and NesC

An open-source operating system designed for wireless embedded sensor networks

Component-based architecture which enables rapid innovation and implementation while minimizing code size

Event-driven execution model

Page 11: Environmental monitoring: from sensors to database

Communication Protocols Design requirement

Energy Efficient Radio communication is the most expensive operation in terms of

energy usage Robust, scalable and adaptive

Dynamic topology changes due to unstable links, node failures and network disconnections

Unique characteristics of our project Long-term operation with very low data rate A single sink node At most of the time, data flow is uni-directional

Layered Architecture Physical/Link Layer Medium Access Control Routing

Page 12: Environmental monitoring: from sensors to database

Physical/Link Layer Radio Propagation

Path Loss - signal strength attenuates as distance to a constant exponent

However, radio connectivity is not a simple disk Shadowing (due to obstructions) and Multipath

Fading Wireless Channel Characteristics

Great spatial variability Non-isotropic propagation Asymmetric links are common due to hardware

calibration

Page 13: Environmental monitoring: from sensors to database

Link Quality Over Space

Packet reception over distance has a heavy tail. There is a non-zero probability of receiving packets at distances much greater than the average cell range

169 motes, 13x13 grid, 2 ft spacing, open area, RFM radio, simple CSMA

Page 14: Environmental monitoring: from sensors to database

Medium Access Control MAC protocol decides when and how nodes access the

shared wireless channel Collision avoidance Duty-cycle control

MAC layer protocols directly controls radio activities, significantly affect the overall node lifetime

MAC in Wireless Networks Contention-based protocols

CSMA/CA – node compete for a single channel On-demand allocation provides more flexibility and adaptivity

Scheduled protocols C/T/FDMA – divide wireless channel into different sub-channels Collision-free and energy-efficient

Page 15: Environmental monitoring: from sensors to database

MAC for Sensors Sources of energy waste in radio communication

Idle listening Costs as much power as transmitting or receiving dominant factor of energy consumption especially in low

data rate systems Collision – retransmit when packets collide

Build on CSMA but also adopt TDMA-like sleep/wakeup duty cycle S-MAC, T-MAC, B-MAC, Z-MAC Reduce idle listen and minimize collision Improve power efficiency while retaining flexibility Sacrifice throughput, increase latency

Page 16: Environmental monitoring: from sensors to database

MAC Protocol Design

Parent … Sync Sleep Rcv 1 Rcv2 Sleep Transmit Sleep

Child 1 … Sync Sleep Transmit Sleep

Child 2 … Sync Sleep Transmit Sleep

We implement a tree-structure data report hierarchy, rooted at the sink node

A global clock is also maintained by time synchronization All nodes begin with a Sync slot

Synchronize time, manage neighbor list, select parent Parent nodes then allocate time slots for their children All nodes are awake, but only broadcasting very short control packets

A node will report its latest readings to its parent in transmit slot, while the parent node will become active and listen to the channel

Nodes sleep for the rest of time

Page 17: Environmental monitoring: from sensors to database

Network Layer - Routing Establishing and maintain the multi-hop

routing hierarchy Link Quality Estimation Neighbor Management

Discover, update, remove neighboring nodes

Parent selection Shortest Path, Minimal Transmission, Geo-

Routing, Energy-Aware routing

Page 18: Environmental monitoring: from sensors to database

Link Quality Versus Distance

1 2 3 4 5 6 7 8 9 100

10

20

30

40

50

60

70

80

90

100Packet Reception Rate vs Distance

Distance (feet)

PR

R (%

)

-25dBm-15dBm

Page 19: Environmental monitoring: from sensors to database

Time Synchronization Why do we need network-wise clock?

Time stamp data samples Set up radio schedule TOA, TDOA in Localization

Pair-wise Synchronization Estimate communication delays

Send time, access time, propagation time, receive time, etc. Estimate clock skew

Perform linear regression on past local/global time pairs Multihop Synchronization Minimize control overhead

Page 20: Environmental monitoring: from sensors to database

Application Layer Energy Efficient Map Interpolation for

Sensor Fields using Kriging (E2K) an energy efficient and error bounded

framework for interpolating maps from sensor fields

Environmental dynamics, such as temperature and soil moisture, are continuous

Should be represented as a continuous surface over the sensor fields through interpolating

Spatial and temporal autocorrelation could be utilized to reduce sample points

Page 21: Environmental monitoring: from sensors to database

Data Interpolating

Page 22: Environmental monitoring: from sensors to database

Data Interpolating

Page 23: Environmental monitoring: from sensors to database

Localization Knowing the exact location where

information was collected is critical A reading is represented by vectors (x,y,t,v)

Self-localization vs Tracking Ranging Methods

Radio, acoustic/ultrasound, laser, etc. RSS, TOA, TDOA Lateration and Triangulation

Page 24: Environmental monitoring: from sensors to database

Solar Harvesting Sub-System Energy Storage Module

Ultra Capacitors and Rechargeable Batteries Choosing Batteries

NiMH, NiCd, Li-ion Solar Harvesting Module

Solar Cells Regulators and Switches

Circuit Design Smart Battery Monitoring Energy-Aware Protocol and Considerations

Page 25: Environmental monitoring: from sensors to database

Over-the-Air Programming Loading a new application or upgrading an existing

application on a sensor node via a serial port or some physical connections to the node Reprogram nodes one by one

However, physical access to nodes is in many cases extremely limited following deployment

Even when access were possible, manually updating hundreds or thousands of nodes would be a tedious task indeed

Network reprogramming protocols have recently emerged as a way to distribute application updates without requiring physical access to sensor nodes.

Page 26: Environmental monitoring: from sensors to database

Multi-hop Over-the-Air Programming

MOAP divides a program image into packets, and these packets are distributed through the network. Once received, packets are placed in stable storage until the entire update has been completed.

In MOAP, sources advertise updated code images to their neighbors. A node having received a full image become publishers and propagate the image to other nodes out of range of the original source. This process is applied iteratively until the update has propagated across the

network. Packet loss and retransmission

Receiver uses a sliding window to keep track of lost packets. When a missing packet is detected, the receiver sends a uni-cast

retransmission request. If the source does not respond within a certain amount of time, the receiver

broadcasts a retransmission request to which all nodes within range reply. This allows the receiver to choose a new source in case the original source fails.

Duplicate requests arriving at a source within a given time period are suppressed.

Page 27: Environmental monitoring: from sensors to database

Cross Layer Protocol Design No standard protocol for sensor nets

Sensor protocol design is task-specific Resource constraints even demand cross-layer

integration While some protocols can achieve very high

performance in terms of the metrics related to each of the individual layer, they are not jointly optimized in order to maximize the overall network performance and minimize energy expenditure

When designing communication schemes, we can not simply pick the best protocol in each layer and pile them up.

Page 28: Environmental monitoring: from sensors to database

Tele-Communication System The needs for telemetry

Provides near-real-time data feeding Enables remote control of sensor nets and data loggers

Change monitoring parameters Update sensor motes/data logger programs after deployment

Single Board Computer (SBC) 200Mhz ARM processor, 64MB RAM, 1GB SD Card Linux support Bridge between sensors and Internet Local Database Server

GPRS modem PPP and PPP Daemon

a data link protocol commonly used to establish a direct connection between two nodes over serial cable, phone line, cellular phone, or dial-up network to get access to the Internet

Page 29: Environmental monitoring: from sensors to database

Conclusion Data flows from sensors to remote

database System Architecture Research areas

Energy-Aware Design Cross Layer Protocol Design Over the air programming Localization

Questions?