A GRICULTURE: A Field for Development using AI Techniques

1. AGRICULTURE: A Field for Development using AI Techniques - Lets Identify the Applications CS621-Artificial Intelligence Course Seminar Presented by: V S K Murthy B (08407403) SingrePawan (07305039) CS621 Course Tutor: Prof. Pushpak Bhattacharya

2. Talk is divided into two parts: • Part-I: • Why to choose “field of Agriculture” ? • Identified Areas for enhancing Agriculture sector • Computational Intelligence in Agriculture and Environment • Part-II: • Intelligent Environment Control for Plant Production • Intelligent Robot in Agriculture • Conclusion CS621-Artificial Intelligence Course Seminar Outline

3. CS621-Artificial Intelligence Course Seminar Part-I

4. Sector status in India • Growth of socio-economic sector in India • Means of living for almost 66% of the employed class in India • Acquired 18% of India's GDP • Occupied almost 43% of India's geographical area • Huge investment made for Irrigation facilities etc. in 11th five year plan • Introduction of de-regulation in agriculture sector • Opens competition for agriculture products • Removal of unnecessary restrictions — movement, stocking, and so on.. • Good price to farmer • Substantial technology growth in coming years CS621-Artificial Intelligence Course Seminar Why to choose “Field of Agriculture”?

5. Any process growth rates can be linked with efficiency curves Due to deregulation, Agriculture has bright future insight CS621-Artificial Intelligence Course Seminar Why to choose “Field of Agriculture”? Philosophy of Efficiency Different Technologies Efficiency curves Time scale

6. Peak in the agricultural sector will again reach in near future CS621-Artificial Intelligence Course Seminar Why to choose “Field of Agriculture”?

7. Needs monitoring on • Agricultural crop conditions • Weather and climate • Ecosystems • Decision support for agricultural planning and policy-making • On the basis of AI interest • Computational Intelligence in Agriculture and the Environment • Optimizing different types of bio-systems • Testing and fitting of quantitative models • Intelligent environment control for plant production systems • Intelligent robots in agriculture • An expert geographical information system for land evaluation • Artificial neural network for plant classification using image processing. • Control of green house. CS621-Artificial Intelligence Course Seminar Identified Areas for enhancing Agriculture sector

8. CS621-Artificial Intelligence Course Seminar Computational Intelligence in Agriculture and the Environment

9. Search procedures • Exhaustive techniques (random walk) • Calculus based methods (gradient methods) • Partial knowledge techniques (hill climbing) • Knowledge based techniques (Production rule systems, heuristic methods) • Stochastic techniques (SA) • Biologically inspired algorithms (GA and immune) • Problems deal with optimizing bio-systems and fitting quantitative models require • Refinement or processing using adaptive search procedures • Bio-system Derived Algorithms (BDAs) • Photosynthetic Algorithm (PA) • Leaf Cellular Automate (LCA) CS621-Artificial Intelligence Course Seminar

10. CS621-Artificial Intelligence Course Seminar Photo-Synthetic Algorithm Atmosphere Light (Stimulation) Oxygen/CO2 concentration CO2 Reservoir • Any problem that can • be solved by GA can • also be solves by • PS Algorithm Benson- Calvin Cycle Photo- Respiration RuBP GAP Copy Good Fitness Discard Poor Next Iteration DHAP (Knowledge string)

11. CS621-Artificial Intelligence Course Seminar Similarities of GA and PA Algorithms Example: In Part-II, Nutrient control set for plant growth has been solved by PS Algorithm

12. CS621-Artificial Intelligence Course Seminar Part-II

13. CS621-Artificial Intelligence Course Seminar Intelligent Environment Control For Plant Production System

14. To increase productivity of crops Care for special herbal valued plants, environment diverse plants etc., which in turn increases our export value To develop decision making support CS621-Artificial Intelligence Course Seminar Why it is required?

15. CS621-Artificial Intelligence Course Seminar Hydroponic System

16. CS621-Artificial Intelligence Course Seminar

17. In plant production, good fruit yield requires an optimal balance between • Vegetative growth (e.g. root, stem, leaf growth) • Reproductive growth (e.g. flower and fruit growth) • NNs and GA provides optimal set points of the nutrient concentration (NC). • The ratio of total leaf length (TLL) to stem diameter (SD) defines as a predictor for plant production growth. CS621-Artificial Intelligence Course Seminar Plant Growth Optimization Problem

18. Let TLL(k)/SD(k) be the time series of TLL/SD as affected by NC(k) (k=1,......,N; N : final day) • Seedling stage(1 ≤ k ≤ N ) divided into four steps: • Transplanting • Vegetative growth after transplanting • Flowering of the first truss • Fruit setting for the first truss and flowering for the second truss. • Consider the value of nutrient concentration at each step is NC1, NC2, NC3, NC4 . {1≤ k ≤ N1L :step1, N1L+1 ≤ k ≤ N2L: step2, N2L+1 ≤ k ≤ N3L : step3, N3L+1 ≤ k ≤ N: step4} CS621-Artificial Intelligence Course Seminar Optimization Problem

19. Objective Function : • Objective Problem Maximize F(NC) Subject to α1 ≤NC(k)≤ α2 CS621-Artificial Intelligence Course Seminar Optimization Problem

20. CS621-Artificial Intelligence Course Seminar Neural Networks

21. CS621-Artificial Intelligence Course Seminar Genetic Algorithm

22. Step1: The Initial population consisting of several individuals • Step2: Several individuals in another population are added to original population to maintain diversity • Step3 : Crossover and mutation operations are applied to the individuals • Step4: Fitness values of all individuals are calculated by NN model • Step5 : Superior individuals are selected and retained for next generation • Step6 : step 2 through 5 are repeated until an arbitrary condition satisfied CS621-Artificial Intelligence Course Seminar Procedure of GA

23. CS621-Artificial Intelligence Course Seminar Intelligent Robots in Agriculture

24. CS621-Artificial Intelligence Course Seminar Strawberry harvesting robot Source: http://www.lovingthemachine.com/2008/04/farmer-hails-strawberry-picking-robot.html

25. CS621-Artificial Intelligence Course Seminar Hortibot robot for weeding Source: http://www.lovingthemachine.com/2008/04/farmer-hails-weeding.html

26. CS621-Artificial Intelligence Course Seminar • Currently, Research on “Agricultural robots” is active in Japan and Korea Displacement of a Robot

27. Need for AI focus on Agriculture sector is discussed Bio-system Derived Algorithms (BDAs) are explored Identified intelligent approaches which are useful for mechanizing complex agricultural systems Growing Research and technology should contribute to the basic amenities in agriculture CS621-Artificial Intelligence Course Seminar Conclusion

28. CS621-Artificial Intelligence Course Seminar [1] D.E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning. Reading, MA: Addison Wesley, 1989. [2] J.H. Holland, “Genetic algorithms,” Sci. Amer., pp. 44-50, July 1992. [3] J.B. Bowyer and R.C. Leegood, “Photosynthesis,” in Plant Biochemistry, P.M. Dey and J.B. Harborne, Eds. San Diego, CA: Academic, 1997, pp. 49-110. [4] N. Kawamura, K. Namikawa, T. Fujiura, and M. Ura, “Study on agricultural robot,” J. Jpn. Soc. Agricultural Mach., vol. 46, no. 3, pp. 353-358, 1984. [5] Y. Hashimoto and K. Hatou, “Knowledge based computer integrated plant factory,” inProc. 4th Int. Cong. Computer Technology in Agriculture, 1992, pp. 9-12. [6] Y. Hashimoto, “Applications of artificial neural networks and genetic algorithms to agricultural systems,” Comput. Electron. Agriculture, vol. 18, no. 2,3, pp. 71-72, 1997. [7] Yasushi Hashimoto, Haruhiko murase, “Intelligent systems for agriculture in japan”. IEEE Control systems Magazine, Oct 2001. References:

29. CS621-Artificial Intelligence Course Seminar Thank You ! Questions??

30. CS621-Artificial Intelligence Course Seminar Photo respiration Photosynthesis pathways of Benson-calvin cycle

31. CS621-Artificial Intelligence Course Seminar