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Sistem za avtomatsko opozarjanje na potrebo po škropljenju v kmetijstvu
Možina, Klemen (Author), Rupnik, Rok (Mentor) More about this mentor... This link opens in a new window

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Abstract
V kmetijstvu vedno strožje zakonodajne omejitve po vsebnosti škropiv v pridelkih in želje po varovanju okolja predstavljajo izziv, kako optimizirati škropljenje, da bo čim bolj učinkovito ob čim manjši uporabi zaščitnih sredstev. Magistrsko delo obravnava zasnovo prototipa integriranega sistema za avtomatsko opozarjanje na potrebo po škropljenju. Z namenom napovedovanja ugodnih trenutkov za škropljenje modeliramo in napovedujemo razvoj opazovanega škodljivca na določenem območju. Za razliko od tipičnih pristopov pri modeliranju razvoja škodljivcev naša rešitev avtomatsko v realnem času iz obstoječega sistema za spremljanje škodljivcev pridobi ustrezne podatke, izračuna napoved razvoja škodljivcev in predlaga najugodnejše termine za škropljenje. Napovedovanje se izvaja znotraj zasnovanega prototipa sistema za podporo odločanju, ki nudi uporabniku prijazen pregled in napoved potencialnih ugodnih trenutkov za škropljenje. Prednost naše rešitve je tudi integracija s sistemom za proženje opozoril, ki omogoča takojšnje opozarjanje na podlagi napovedi škropljenj in pregled opozoril na terenu z uporabo zasnovane mobilne aplikacije.

Language:Slovenian
Keywords:škropljenje, kmetijstvo, sistemi za podporo odločanju, sistemi za opozarjanje
Work type:Master's thesis/paper (mb22)
Organization:FRI - Faculty of computer and information science
Year:2020
COBISS.SI-ID:1538517187 Link is opened in a new window
Views:45
Downloads:18
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Secondary language

Language:English
Title:An automatic alerting system for the need for spraying in agriculture
Abstract:
In agriculture, increasingly strict regulatory restrictions on the pesticide residues in crops and the desire to protect the environment present a challenge of optimizing spraying to become as efficient as possible while minimizing the use of protective measures. The thesis deals with designing a prototype of an integrated system for automatic alerting for the need for spraying. In order to predict favorable dates for spraying, we model and predict the development of the observed pest in a particular area. Unlike typical pest development modeling approaches, our solution automatically obtains relevant data from an existing pest monitoring system in real time, calculates a pest development forecast and suggests the most favorable dates for spraying. The forecast is performed within a designed prototype of a decision support system that provides a user-friendly overview and forecast of potential favorable dates for spraying. The advantage of our solution is also the integration with an automatic alerting system, which offers immediate alerting based on spraying forecasts and the review of alerts on the field using a designed mobile application.

Keywords:spraying, agriculture, decision support systems, alerting systems

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