Presentation on theme: "Semantic Web Technologies for Orchard Irrigation Systems Jiao Tao, Rui Huang, Shangguan 2008/11/17 1."— Presentation transcript:
Semantic Web Technologies for Orchard Irrigation Systems Jiao Tao, Rui Huang, Shangguan 2008/11/17 1
Outline Motivation Use Case Knowledge Representation Implementation Conclusions 2
Motivation Many orchards use traditional irrigation systems Measure soil water content manually Treat different fruit trees in the same way Treat different soil in the same way Irrigation technology is orchard specific Actually, irrigation is not just spraying water. It needs a lot of knowledge from different domain Botany: fruit, growth stage, root depth Agrology: soil texture, soil water content, soil allowable depletion Climatology: precipitation, evapotranspiration We need smart irrigation systems which know whether we should water the orchard. 3
Motivation Semantic e-Science works here! Integrating data from multiple data sources Soil water content from sensor Evapotranspiration rate based on history record Precipitation rate from weather forecast services … Infer Fuji is apple and Pantao is peach, thus they have different evapotranspiration rate Semantic Mediawiki as a quick prototype development platform 4
Use Case Provide an irrigation system which decides whether irrigation is necessary for a given field, if necessary how much water is needed, and the next day (possible) to water. 5
Knowledge Representation 9 Field Capacity: amount of water can be held in soil Permanent Wilting Point: the point at which the water in soil is not available for uptake by plant roots. Plants die at this point. Available Water: amount of water held in the soil between field capacity and permanent wilting point. Allowable Depletion: the point where plants begin to experience drought stress. Usually it is 50% of total available water.
Knowledge Representation General Irrigation Knowledge Managing irrigation = managing money Balance: soil water content Input: precipitation, irrigation Expense: evapotranspiration The goal of a well-managed irrigation system is to maintain soil moisture between field capacity and allowable depletion. And, Water holding capability depends on soil texture, root depth Evapotranspiration depends on locations, seasons, crop, growth stage Usually sensor reads water potential, not water content 10
Knowledge Representation Our irrigation model S: sensor reading, current water content R: rainfall in next week T: threshold (soil allowable depletion) U: upper bound of water holding capability Ev.: evapotranspiration rate per week of given crop ConditionWater? (Y/N)Water VolumeNext Day to Water (1)S < T S + R < UYU-S-R(U-T)/Ev. S + R > UY(N)0(U-T)/Ev. (2)S > T S + R < UNN/A(S+R-T)/Ev. S + R > UNN/A(U-T)/Ev. 11
SMW based Implementation Based on Tetherless Map extension 16
Demo Workflow User logs into the system Select kinds of fruits Check whether irrigation is needed for a certain orchard field Currently only supports checking one field per time Be informed about irrigation volume and next irrigation day
Irrigation Model Implementation Simple Math Calculations Calculation procedures implemented within templates (functions/methods) Retrieve multiple parameter values using SMW inline queries (variable definitions) Do mathematical calculations with the help of SMW parser functions (programming language syntax)
Project Experiences Semantic Mediawiki (SMW) as a quick prototype platform SMW is able to support simple mathematics (limited, but can be extended via extensions) How to create ontology with large number of classes/instances in bulk on Wiki (import/export) How to integrate multiple data services from other portals (e.g., weather forecast, rainfall, etc) using Wiki How to forge sensor data (possibly customized parser function)
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