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Title:Avtomatizacija namakalnega sistema s programom Home assistant : magistrska naloga
Authors:ID Lukan, Matej (Author)
ID Kolar, Janez (Mentor) More about this mentor... New window
Files:.pdf MAG_Lukan_Matej_2025.pdf (21,85 MB)
MD5: C2DEECFA7723DDF15039328CCA0B735C
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FIŠ - Faculty of Information Studies in Novo mesto
Abstract:Pametni namakalni sistemi postajajo ključni za učinkovito upravljanje voda, saj zahtevajo podnebne spremembe in naraščajoča potreba po trajnostnih rešitvah optimizacijo zalivanja. V magistrski nalogi je razvit sistem avtomatiziranega namakanja s programom Home Assistant, ki temelji na senzorjih vlage v tleh. Cilj je zmanjšati porabo vode in izboljšati rastne pogoje rastlin z avtomatskim prilagajanjem namakanja na podlagi dejanskih potreb. Raziskava je pokazala, da je Home Assistant bolj prilagodljiv in cenovno ugodnejši v primerjavi s komercialnimi rešitvami, vendar zahteva več tehničnega znanja pri konfiguraciji. Rezultati potrjujejo, da avtomatizirano namakanje optimizira porabo vode, zmanjšuje potrebo po ročnem zalivanju in izboljšuje trajnostno upravljanje rastlin. Nadaljnji razvoj bi lahko vključeval uporabo umetne inteligence za analizo zgodovinskih podatkov, kar bi še dodatno optimiziralo namakalne urnike.
Keywords:Home Assistant, avtomatizacija namakanja, pametni namakalni sistemi, optimizacija vode, senzorski sistemi
Place of publishing:Novo mesto
Place of performance:Novo mesto
Publisher:M. Lukan
Year of publishing:2025
Year of performance:2025
Number of pages:XXI, 125 str.
PID:20.500.12556/ReVIS-11755 New window
COBISS.SI-ID:238526723 New window
UDC:004.42:681.5:631.67(043.2)
Note:Na ov.: Magistrska naloga : študijskega programa druge stopnje;
Publication date in ReVIS:06.06.2025
Views:68
Downloads:1
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.

Secondary language

Language:English
Abstract:Smart irrigation systems are becoming essential for efficient water management as climate change and the need for sustainability drive the optimization of watering practices. This thesis presents an automated irrigation system using Home Assistant, based on soil moisture sensors, aimed at reducing water consumption and improving plant growth by adapting irrigation schedules to actual needs. The study demonstrates that Home Assistant offers greater flexibility and cost-effectiveness compared to commercial solutions, though it requires more technical expertise for configuration. Results confirm that automated irrigation optimizes water use, reduces manual watering requirements, and enhances sustainable plant management. Future developments could include artificial intelligence for historical data analysis, further improving irrigation schedules.
Keywords:Home Assistant, irrigation automation, smart irrigation systems, water optimization, sensor systems


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