Social Media Chatbot System - Beekeeping Case Study

Latioui, Zine Eddine; Bougueroua, Lamine; Moretto, Alain

doi:10.1007/978-3-030-14347-3_29

Cited by 4 publications

(5 citation statements)

References 10 publications

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“…Estudos que visam aplicar técnicas de processamento de imagens em diferentes áreas do conhecimento podem ser encontrados em [11]. Além disso, a utilização da Inteligência Artificial de modo geral tem sido empregada em tarefas que visam uma melhora no processo de manejo da Apicultura [12,13,14].…”

Section: Estado Da Arteunclassified

SEGBEE: Mobile Application for Honey Segmentation in Apiary Boards

Rocha

Melo

Oliveira

2022

RITA

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Beekeeping is one of the most important activities for humans. Since ancient times, honey has been used in the treatment of several diseases and is an extremely powerful antioxidant. The process of visual analysis of the apiary requires trained specialists who try to obtain relevant information to make a decision about what to do with the honeycomb. Since the process is performed manually, given the complexity of the task, opportunities arise for the application of automated systems that can assist the beekeeper's decision making. Thus, this paper presents the development of the application \textit{SegBee}, a computational tool that performs the segmentation in the apiary plates, where there is the presence of honey, in an accessible, fast and practical way. To do this, the OpenCV library was used for the digital image processing part, and the Kivy library was used to develop the interface of the mobile application. The tests performed showed that the images were adequately segmented by \textit{SegBee}, indicating where the honey is located on each analyzed plate. A visual comparison was made between results obtained by \textit{SegBee} and another commercial application, demonstrating the effectiveness of the developed tool. The proposed solution contributes to the improvement of the beekeeping professionals' work, once the application is simple to use and fast to process, being able to help in the honey identification task in apiaries plates.

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Section: Estado Da Arteunclassified

SEGBEE: Mobile Application for Honey Segmentation in Apiary Boards

Rocha

Melo

Oliveira

2022

RITA

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“…The important question raised by this article is the use of external data to build decision support systems. More recently, text mining and deep learning are used for assisting beekeepers during the process of taking care of their apiary [10].…”

Section: Beekeeping and Iotmentioning

confidence: 99%

“…The beekeeping industry faces many problems related to the health of bee colonies concomitant with a general decline in production. Scientific work focused on understanding these phenomena has allowed identifying several causes and establishing concrete elements to guide the decisions of beekeepers [10].…”

Section: Introductionmentioning

confidence: 99%

Toward an Intelligent System Architecture for Smart Agriculture: Application to Smart Beehives

Huet

Bougueroua

Kriouile

et al. 2021

Advances in Intelligent Systems and Computing

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Since the application of information and communications technologies (ICT) to agriculture is far from the potential, we investigate how to systematize the process of transformation. In this article, we propose a new approach to design intelligent systems for the management and supervision of smart agriculture, as well as an example of its application in the beekeeping sector. It consists of the analysis of all the decisions that can be made using a spatio-temporal matrix that couples the time horizons to the modeling approaches. The final goal is to develop a reusable architecture for smart agriculture.

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“…Beekeepers grapple with many issues related to the health of bee colonies. Scientific work is focused on a deep understanding of the causes of these phenomena in order to help beekeepers make the right decisions [1].…”

Section: Introductionmentioning

confidence: 99%

Digital Transformation of Beekeeping through the Use of a Decision Making Architecture

et al. 2022

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The use of information and communication technologies (ICT) in agriculture is far from their potential. In this article, we consider how to facilitate and systematize the process of transforming traditional agriculture into digital agriculture; Agriculture 4.0. Among the different technologies, we focus on the IoT aspects. In the article, we propose a new approach for the design of intelligent agricultural management and supervision systems. The proposed approach is illustrated as an example of application in the beekeeping sector. Indeed, this sector is affected by a crisis due to the disappearance of bees and the different actors need support to make their decisions. As an example of decisions that can be made, we can cite: treatment planning or policy planning. An architecture based on sensors and open data is proposed to help them make decisions. An implementation of it is shown; it is based on a device with sensors, as well as an interface to collect the data on beehives and show notifications and alerts to beekeepers. The proposed architecture is flexible, and it can be used in the context of different levels of technology maturity. The final objective is to develop a reusable architecture for Agriculture 4.0.

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Social Media Chatbot System - Beekeeping Case Study

Cited by 4 publications

References 10 publications

SEGBEE: Mobile Application for Honey Segmentation in Apiary Boards

SEGBEE: Mobile Application for Honey Segmentation in Apiary Boards

Toward an Intelligent System Architecture for Smart Agriculture: Application to Smart Beehives

Digital Transformation of Beekeeping through the Use of a Decision Making Architecture

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