Sensor Network Applications in Rural Areas. Arun Jose CSRE, IIT BOMBAY

Transcription

1 WELCOME

2 Sensor Network Applications in Rural Areas Arun Jose CSRE, IIT BOMBAY

3 INTRODUCTION Issues and problems in rural areas Technology transfer and sustainable development are needed For decision making timely data collection is essential The current level of data collection is not efficient and sufficient Sensor Network Technology helps in obtaining data in real time mode

4 System architecture

5 System architecture Standard construction of Wireless Sensor Network in an agricultural ral field (Source: Fukatsu et al.,2004)

6 Sensor Network Sensors Wireless LAN Camera Web Server Power source

7 Sensors available 1. Air-Temperature 2. Relative Humidity 3. Solar Radiation 4. Soil Moisture in 3depths(Surface,10 cm & 30cm) 5. Soil Temperature in 3 depths 6. Wind Speed 7. Leaf Wetness 8. Air-Pressure 9. CO 2 Concentration 10. N,P, and K concentration

8 Wireless LAN A wireless LAN provides a high-speed transmission network for the data collected by the sensors.

9 Camera

10 Web server Web server is a software which gives Web information to a client We can access the web server by using web browser such as Internet Explorer

11 Power Sources

12 Ubiquitous Networking using Sensor Network Field or Forest Greenhouse house FTTH,ADSL i-space Mountain Amenity farm Fishing spot Organic farm Farmer's market Farm inn Camping site Farmer's restaurant FiledServer Wireless relay communication Hotspot (Source: cuments/cigr2004paper.pdf)

13 Commercial Sensors Solar Radiation Sensor Devices inside Body CPU Wireless LAN Card Memory Network Camera Temp. Sensor, Humidity Sensor Ventilation Outlet

14 Sensors with Solar Panels (Source: (Source:

15 Sensor installed at IITB

16 Agricultural Sensor Network installed in Sula Vineyard (Source

17 APPLICATIONS OF SENSORS IN RURAL AREA (1) Environmental monitoring (2) Agriculture (3) Food industry (4) MetBroker

18 1. Environmental monitoring o For weather monitoring o For the optimal use of fertilizers in the field

19 2. Agriculture 2.1 Precision agriculture 2.2 Green house applications 2.3 Farm machinery automation 2.4 Poultry and animal husbandry applications

20 2.1 Precision agriculture Doing the right thing, in the right place, in the right way, at right time in agriculture Needs modern technology

21 Precision Agricultural Cycle (Source: /sag1 951?opendocument)

22 Application of Sensors in Precision Agriculture Spatial data collection Precision irrigation Precision fertigation and Disease and insect pest management

23 Spatial data collection soil water availability soil fertility leaf area index leaf temperature leaf chlorophyll content plant water status local climate data insect-disease disease-weed infestation grain yield, etc.

24 Precision irrigation Water is very scarce To conserve water and to increase the yield Sensors are very useful in irrigation scheduling

25 Precision Fertigation Fertilizer should be applied at proper time and in proper quantity By using sensors, we can achieve very high application efficiency

26 Disease and Insect Pest Management Digital camera attached with the sensor will continuously monitor the crop By knowing leaf wetness we can forecast the diseases By using web server we can provide information on pest and disease infestation

27 2.2 Green house applications To monitor temperature, relative humidity, and CO 2 concentrations inside the green house

28 2.3 Farm machinery automation Mobile Sensor

29 3. Food Industry Applications Real time temperature measurement for - thermal sterilization, irradiation, etc Bacterial concentration in food products can also be sensed

30 4. Application of Field Servers in MetBroker MetBroker - MetBroker is a middleware for weather data that provides agricultural models with consistent access to many different weather databases Sensors can be used as a data input in MetBroker Real time data can be accessed using internet enabled cellular phones

31 Components of MetBroker (Source: Slide 50

32 Remote Sensing Data Field Server Data GPS Data Models Geographic Information System Decision Making

33 Thank You