The ClearAnswer Solutions Series

1

Effective Use of Smart Sensors in Digital
Governance
January 14-16, 2008 / Bangkok Thailand
Rajan Zambre, CEO/CTO CEO/CTO, Erallo
Technologies, Inc., USA Dr. Ganapati P. Patil
Distinguished Professor, Pennsylvania State
University, USA Mr.Vijay Singhal, District
Collector, Jalgaon, Maharashtra, India Dr.
Sharad Joshi Professor, Slippery Rock University,
Pennsylvania, USA
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Contributors

• Rajan Zambre
• CEO/CTO, Erallo Technologies, Inc.
• 20 Taylor Street, Littleton, MA 01460
• www.erallo.com zambre_at_erallo.com
• Dr. G.P. Patil
• Distinguished Professor of Mathematical
  Statistics 
• Professor of Mathematical and Environmental
  Statistics,
• Pennsylvania State University, Pennsylvania,
  U.S.A.
• gpp_at_stat.psu.edu
• Mr. Vijay Singhal
• District Collector
• Jalgaon District, State of Maharashtra, India
• Dr. Sharad W. Joshi
• Professor, Slippery Rock University, Pennsylvania
• sharadchandra.joshi_at_sru.edu

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Overview

• Presentation Discussion
• Data collection data reporting for digital
  governance
• Sensors Sensor Nodes Sensor Networks
• Applications in digital governance
• Integrated water management
• Farm advisories
• Applications remote health monitoring
• ICDS

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Digital Governance

• Data Flow
• many, many, manual steps prone to errors, delays,
  tampering

WEB access for public
administrators, policy makers
decision support systems
manual data entry
more levels of data transfer, supervisory levels,
compilation
manual data transfer (phone, paper, fax...)
manual data collection
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Digital Governance

• Data Flow with Sensors
• automated collection, transfer, reporting

WEB access for public
administrators, policy makers
decision support systems
automated data
transfer, compilation and processing
automated
data measurement and recording
automated data entry

• Reduces
• tedious manpower tasks
• measurement and reporting errors
• scheduling problems, time delays
• data entry tasks, data tampering

sensors
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Sensors

• Devices to measure/detect real-world conditions
• Analog sensors
• Digital sensors
• Sensor controls

CO2 Sensor
Ethanol sensor to measure transdermal alcohol
levels
Soil Moisture Meter Gypsum Blocks
Frequency Domain Reflectometry (FDR) to measure
water content of soil
Neutron sensor to measure soil moisture
Tipping bucket rain gauge
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Smart Sensors
Smart Sensor Node
sensor device connectivity, processor,
memory, battery
Sensor
Smart Node
Wireless Radio Processor, Memory, Battery
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Sensor Node Data Logger
to Central Unit (laptop, PC...) and other Data
Loggers
Data Logger card (off-the-shelf card -- size of
a stick of gum)
Data Logger Module Specs Memory up to 4
GB Processor Intel PXA 270 CPU Speed 600
MHz Connectivity Bluetooth WiFi Operating
System Linux Weight of PCB 1 oz Size of PCB
80mm x 20mm
WiFi
Bluetooth
Bluetooth
Sensor Module (custom)
Sensor Module
Bluetooth
. . . . . . . . . .
1 . . . . . 8
Analog ON/OFF switch
Power Relay Control Switch for Digital Sensors
Sensor Module Specs of Analog Ports 8 Analog
Precision 16-24 bits of Serial Ports 3
of Serial Relays 1 of Analog Switches
1 Connectivity Bluetooth Operating System
Linux Weight of PCB 1-2 oz
8 port ADC
3 digital serial ports
UAV Data Loggers and Sensor Nodes
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Sensor Network Component
RF -- WiFi/802.11...
cellular, satellite...
Bluetooth
cable modem, phone modem...
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Ad-hoc Sensor Network
Sensor Node
Sensor Node
Router Node
Sensor Node
to Wide Area Network connectivity
Gateway Node
Router Node
Sensor Node
Sensor Node
Ad-hoc networks self-configuring, self-healing,
multi-sensor data fusion
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Connectivity
Sensor Network
Gateway
Sensor Network
Gateway
Transmit Network
Database
DSS Applications
Central Unit
data recording
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Backend Connectivity
sensor network controller with cell phone
connectivity
weather station with cell phone connectivity
usb enabled cell phone used for backend
connectivity
linux open source cell phone module
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Software Components

1. Radio Node Software
2. Base Station, Data Logger Software
3. Management Software, GUI interface

Central Unit
Base Station
Radio Node
Analog
Data Processing Commands
Data Base Sensor Node Mgt
Wide Area Network
Sensors
Sensor Comm
Radio Comm
Radio Comm
Digital
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Low Cost Network Scenario
Bike Receiver RF radio, CPU, memory communicates
with Data Logger/Base Stations
Data Logger/Base Station RF radio, CPU,
memory communicates with Sensor Nodes and Bike
Receiver
Ad-hoc Network of Radio Nodes RF radio,
processor, ADC, memory communication between
other nodes and BaseStation
to Central Unit
Soil level
Range 100 feet to ½ mile, depending on radio type
Water table
Pressure Transducer Sensors
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Jalgaon District, India
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Jalgaon Projects

• Smart Sensor Applications Planned
• Integrated Child Development Scheme (IDCS)
• Integrated Water Resource Management
• Micro-weather Station Network
• Farmer Advisory Network

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1. Integrated Child Development Scheme

• UNICEF Program
• Promote childhood survival
• Provide integrated set of basic health services
  to children 0-6, pregnant women, and nursing
  mothers,
• Childrens weight and age are monitored to ensure
  they dont fall below standards
• Administrated through community-based childcare
  centers (in India, called Anganwadi Centers)

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Improve Process
1. Weigh child -- weight, height, name
2. Anganwadi center village level record on
paper duplicate/triplicates
3. Supervisor (ICDS worker) -- village level
adds date
4. Child Development Project Officer (CDPO) --
sub-district level
5. Deputy Chief Executive Officer district
level
6. District Collector district level
7. State program level
8. National program level
Simple sensor technology could improve data
accuracy and dates, reduce data tampering, reduce
delays, save money, improve planning and
allocation of funds/resources save lives
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ICDS Sensor Network
PDA (optional)
Digital weight scale
automated transmission using RF
Internet/ Web Services dialup or cellular
Base station at Anganwadi center
Central Unit
Finger print scanner
Digital weight scale sensor node integrated
with finger print scanner automated recording
and wireless transmission of data
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Child Mortality Data File
Typical Data File Child Mortality Data
0 3138 111 1 3 5 1 2206 90 0 2 5 6 2
3558 159 1 6 7 3 2303 85 0 4 5 8 4 1455
48 3 5 8 9 5 2088 91 0 1 3 4 6 9 11
12 6 2762 92 1 2 5 7 12 7 2086 62 2 6 8
2774 117 3 4 9 10 13 9 1547 42 4 5 8 10
11 10 2411 91 8 9 11 13 11 2706 112 5 9 10 12
13 12 4679 170 5 6 11 13 3334 138 8 10 11
Data File Structure Column 1 Cell (Tehsil)
ID Column 2 Live births Column 3 Deaths 0 to 6
years Column 4 onward IDs of cells
adjacent to the given cell
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Child Mortality Hotspot
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Infant Mortality Hotspot
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Rural Population Hotspot
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Tribal Population Hotspot
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Rural Population Data
ULSScan Tree for Rural Population Data
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2. Integrated Water Resource Mgt

• Components to Integrated Water Management
• Rainfall monitoring
• Dam/reservoir monitoring
• Inspection well monitoring
• Water quality monitoring
• Primary Goals
• Effectively manage water usage for public and
  agro-industry
• Provide pre-emptive disaster management and
  services

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Water Resource Problems

• Measurement, reporting, and entry of data all
  error prone
• No synchronization of dam overflow and rain fall
• Waste of growingly scarce resources
• Excessive use of water, lowering water table
• Need better data for more effective
  planning/managing

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Integrated Sensor Network
for Water Resource Management
Gateway
Gateway
weather sensors
dam level sensors
rain gauge sensors
inspection well sensors
Gateway
Sensor Nodes
DSS Applications
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Sensor Technologies
Hydrostatic pressure sensor
Hydrostatic water pressure probe
Tipping bucket rain gauge
Nitrate ion-selective electrode
Water Level Dataloggers
Fluoride Ion-selective electrode
Submersible Pressure Level Transducer
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3. Micro-weather Station Sensor Network

• Currently
• Jalgaon district 11,765 sq kilometers
• Over 780 villages on river banks
• Weather monitoring only done at district level
• Doesnt provide granularity or precision for
  emergency warning services
• Flood of 2006 emergency services were not
  delivered in time due to lack of data

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Sensors for Early Warning

• Need
• Network of low cost, commercially available
  weather stations
• Integrated with micro-processors and
  communications devices
• Distribute throughout the district
• Benefit
• Provide timely warnings
• before damage to property or loss of life occurs
• Speed resources to areas for recovery
• Integrate with water management network

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4. Farmer Advisory Network

• Need up-to-date information
• Water availability, irrigation forecasts, pumpage
  yeild
• Weather forecasts
• Current soil conditions (N,P,K)
• Water quality organic inorganic
• Disease forecasts

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Sensor Data for Farming

• Benefits
• Aid in cropping decisions
• Increase crop yields
• Reduce disease
• Correctly plan for irrigation forecasts
• Accurately plan for fertilization
• Plan for seed availability

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Next Steps
Discussion / Questions
Thank You !
Rajan Zambre, CEO/CTO, Erallo Technologies, Inc.
zambre_at_erallo.com Dr. G.P. Patil, Distinguished
Professor, Pennsylvania State University gpp_at_stat.
psu.edu Mr. Vijay Singhal, District
Collector Jalgaon District, State of Maharashtra,
India Dr. Sharad W. Joshi, Professor, Slippery
Rock University, Pennsylvania sharadchandra.joshi_at_
sru.edu