Effective Use of Smart Sensors in Digital Governance

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

2. Contributors Rajan Zambre CEO/CTO, Erallo Technologies, Inc. 20 Taylor Street, Littleton, MA 01460 www.erallo.com; zambre@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@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@sru.edu

3. Overview RF Radio Node 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

4. 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

5. 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

6. 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

7. Smart Sensors Smart Sensor Node = sensor device + connectivity, processor, memory, battery Sensor Smart Node Wireless Radio Processor, Memory, Battery

8. 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

9. Connectivity Sensor Network Gateway Sensor Network Gateway Transmit Network Database DSS Applications Central Unit data recording

10. Software Components • Radio Node Software • Base Station, Data Logger Software • 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

11. 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

12. Jalgaon District, India

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

14. 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, • Children’s weight and age are monitored to ensure they don’t fall below standards • Administrated through community-based childcare centers (in India, called Anganwadi Centers)

15. 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

16. 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

17. 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

18. Child Mortality Hotspot

19. 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

20. 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

21. Integrated Sensor Network Transmit network Central Unit data recording for Water Resource Management Gateway Gateway weather sensors dam level sensors rain gauge sensors inspection well sensors Gateway Sensor Nodes DSS Applications

22. 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 • Doesn’t provide granularity or precision for emergency warning services • Flood of 2006 – emergency services were not delivered in time due to lack of data

23. 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

24. 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

25. Sensor Data for Farming Soil Moisture Sensor Benefits: • Aid in cropping decisions • Increase crop yields • Reduce disease • Correctly plan for irrigation forecasts • Accurately plan for fertilization • Plan for seed availability

26. Next Steps Discussion / Questions Thank You ! Rajan Zambre, CEO/CTO, Erallo Technologies, Inc. zambre@erallo.com Dr. G.P. Patil, Distinguished Professor, Pennsylvania State University gpp@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@sru.edu