Towards Smart Microfarming in an Urban Computing Continuum

Fuente: arXiv
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Hauptverfasser: Grunewald, Marla, Bensalem, Mounir, Dizdarević, Jasenka, Jukan, Admela
Format: Preprint
Veröffentlicht: 2024
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author Grunewald, Marla
Bensalem, Mounir
Dizdarević, Jasenka
Jukan, Admela
author_facet Grunewald, Marla
Bensalem, Mounir
Dizdarević, Jasenka
Jukan, Admela
contents Microfarming and urban computing have evolved as two distinct sustainability pillars of urban living today. In this paper, we combine these two concepts, while majorly extending them jointly towards novel concepts of smart microfarming and urban computing continuum. Smart microfarming is proposed with applications of artificial intelligence (AI) in microfarming, while an urban computing continuum is proposed as a major extension of the concept towards an efficient Internet of Things (IoT) -edge-cloud continuum. We propose and build a system architecture for a plant recommendation system that uses machine learning (ML) at the edge to find, from a pool of given plants, the most suitable ones for a given microfarm using monitored soil values obtained from IoT sensor devices. Moreover, we propose to integrate long-distance LongRange (LoRa) communication solution for sending the data from IoT to the edge system, due to its unlicensed nature and potential for open source implementations. Finally, we propose to integrate open source and less constrained application protocol solutions, such as Advanced Message Queuing Protocol (AMQP) and Hypertext Transport Protocol (HTTP) protocols, for storing the data in the cloud. An experimental setup is used to evaluate and analyze the performance and reliability of the data collection procedure and the quality of the recommendation solution. Furthermore, collaborative filtering is used for the completion of an incomplete information about soils and plants. Finally, various ML algorithms are applied to identify and recommend the optimal plan for a specific microfarm in an urban area.
format Preprint
id arxiv_https___arxiv_org_abs_2408_02992
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Towards Smart Microfarming in an Urban Computing Continuum
Grunewald, Marla
Bensalem, Mounir
Dizdarević, Jasenka
Jukan, Admela
Networking and Internet Architecture
Signal Processing
Microfarming and urban computing have evolved as two distinct sustainability pillars of urban living today. In this paper, we combine these two concepts, while majorly extending them jointly towards novel concepts of smart microfarming and urban computing continuum. Smart microfarming is proposed with applications of artificial intelligence (AI) in microfarming, while an urban computing continuum is proposed as a major extension of the concept towards an efficient Internet of Things (IoT) -edge-cloud continuum. We propose and build a system architecture for a plant recommendation system that uses machine learning (ML) at the edge to find, from a pool of given plants, the most suitable ones for a given microfarm using monitored soil values obtained from IoT sensor devices. Moreover, we propose to integrate long-distance LongRange (LoRa) communication solution for sending the data from IoT to the edge system, due to its unlicensed nature and potential for open source implementations. Finally, we propose to integrate open source and less constrained application protocol solutions, such as Advanced Message Queuing Protocol (AMQP) and Hypertext Transport Protocol (HTTP) protocols, for storing the data in the cloud. An experimental setup is used to evaluate and analyze the performance and reliability of the data collection procedure and the quality of the recommendation solution. Furthermore, collaborative filtering is used for the completion of an incomplete information about soils and plants. Finally, various ML algorithms are applied to identify and recommend the optimal plan for a specific microfarm in an urban area.
title Towards Smart Microfarming in an Urban Computing Continuum
topic Networking and Internet Architecture
Signal Processing
url https://arxiv.org/abs/2408.02992