Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Keynote address 3 seishi
1. ICT in Agriculture – Lessons learned in Asia
Seishi Ninomiya
The University of Tokyo
2. Agriculture was successful in 20th century
1961 2003
• Wheat 1.1 t/ha 2.9 t/ha (2.7 times)
• Rice 1.9 t/ha 4.0 t/ha (2.1 times)
• Corn 1.9 t/ha 4.7 t/ha (2.4 times)
• Population
3 billion 6.3 billion (2.1 times)
• Labor (hrs/ha)*
1,750 hrs 250hrs (1/7th)
FAO statistics * Case of Japan
1 ha = 2.5 acre
3. But its sustainability is being terrified
because the success depended on chemicals and high
resource consumption, resulting in
• Serious impacts on environment
– Water pollution and shortage
– Damage on ecosystem
– Degradation of soil
– CO2 emission in total
• Food safety and reliability issues
In addition, climatic change and frequent extreme
weather are destabilizing crop productivity
4. Agriculture in 21st century
• Food shortage crisis
– Population increases by 200,000 per day
– Usage of food for bio-fuel
– Meat consumption increase
– Unstable and short water supply
– Land shortage and degradation
– Damage by global warming and frequent extreme whether
conditions
• Real sustainability of food production
– Paradigm shift from maximization to optimization
– High productivity
– Profit performance
– Low impact on environment
– Sustainable resource management
– Food safety
– Robustness and best management against global warming
5. An example of such optimization
• Reduction of pesticide application results in
– Cost reduction
• Material cost, labor cost
– Lower impact on environment
– Lower CO2 output
– Food safety and reliability
• To reduce pesticide
– Timely and pinpoint protection (application)
• For timely and pinpoint protection
– Prediction of pest emergence
– Optimal crop management
6. ICT helps optimization in many aspects
• Sustainable agriculture
– Optimal agro-chemical application
– Optimal energy saving
• Cost reduction and competitive agriculture
– Optimal farm planning, efficient management of large number of fields
– Efficient distribution of products
• Robust and stable farm production under extreme weather and
global warming
– Optimal crop / variety recommendation, optimal cropping timing
– Early warning system of extreme weather
• Food safety and reliability
– Tractability, right use of pesticide
– GAP risk management
• High quality products
– Quality sensing and optimal crop management
6• Acceleration of agricultural research
7. Challenges in technologies
• Site-specific data acquisition
– Spatially high resolution data
– Efficient ground data monitoring
• Decision model tuning/assimilation and evaluation
• Agricultural cloud to share data and applications
– Platform to exchange data seamlessly
• Spatial and temporal data integration
• Data standardization
• Multilingual system to share data among countries and
regions
8. Integration of low cost sensor networks
A farm,
Hokkaido
University of Florida JICA Project, Beijing Spinach farm, Chengmai Tomato green house
Orange farm,
Arida Orange farm,
kumano
Rain fed paddy, Khon Kaen Coffee farm, Hawaii
Pasture Imja Glacier Lak, Nepal
Rice paddy, NARC
9. Airborne pest immigration prediction – an
example of data integration
• Weather forecast to predict stream speed and direction
• Particle diffusion model to predict insect dispersion
• Identification taking-off origin
– Inverse simulation based on insect trap data to find
candidates locations of origins
– Satellite image analysis to identify paddies of origins among
candidates
– Crop growth model to estimate rice growth stage 4 mm
• Insect behavior model to estimate taking-off time Rice Hopper 3 mg
Immigration Route
11. The last one mile issues
• Lingual illiteracy
– How to communicate with them?
• ICT illiteracy
– How to extend ICT in rural area?
• Lack of site-specific information
– How to provide it for most optimal site-specific decisions?
• Shortage of extension staffs
– Who provides proper advices?
• Difficulty to realize extensibility of the approach to
different language
12. Youth Mediated Communication Model
（ YMC ）
• A totally new approach of decision support system
to solve the last one mile issues with illiterate
farmers
• Communication with illiterate farmers through
children being educated at schools
• Site-specific field information acquisition by children
• To compensate the lack of local experts by remote
experts
• An way to extend ICT in rural area through educating
children
• A trial to provide internationally extensible
mechanism
12
20. Q & A mechanism
• Typical questions and corresponding answers are
provided in advance as a Q & A sets
– About 250 sets at the beginning
– So-called recipe cards are provided corresponding to typical
answers
– Qs & As are not simply one-to-one so that experts need to
interact
• Children can also consult experts with free text
questions when they cannot find proper ones in the
Q&A sets
– The interactions between children and experts are used to
enrich the Q&A sets
• Questions go along with field data by children
24. Youth Sensors
• Youths’ sensors will provide spatially high density
weather information
– Low cost and maintenance free
– Outlier can be easily found
– Very useful for reliable decision support
• The collected data can be used for an early warning
system
– e.g. Emergence of rice blast
– GIS can be a good interface
• Long-term continuous observation makes decision
support more reliable
– By overcoming site-specificity of agriculture
26. Conclusions
• YMC approach seems to work fine in advising illiterate
farmers though we need to continue the trial for some
more cropping seasons to give the evaluation
• Youths’ sensors help the experts to provide proper
advices
• Children became more interested in agriculture than
before and have more communication with parents
27. Thank you very much
Seishi Ninomiya snino@isas.a.u-tokyo.ac.jp
27
28. Agriculture and world population
10
6.5billion
10
Agriculture
0.5billion
Population
7 Tools
10 (implements
and fire)
5million
20th century
15000
4
10 6 5 4 3 2
1 10 10 10 10 10 10
Years ago
Revised from Robert W.Kate(1994)
