Internet of Things for Electronic Markets

Manogaran, Gunasekaran; Chilamkurti, Naveen; Hsu, Ching‐Hsien

doi:10.1007/s12525-021-00468-1

Cited by 8 publications

(2 citation statements)

References 10 publications

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“…The commerce field that at the moment remains out does not pose special challenges. Studies that have already appeared have underlined the beneficial effects that the IoT can play in connection with central topics of the digital market such as Inventory management, Supply chain management, and Personalization based on consumer preferences (Manogaran et al, 2021). ThingsBoard has features suitable for providing support in each of these application areas (Held et al, 2022).…”

Section: Resultsmentioning

confidence: 99%

Papers Mentioning Things Board: A Systematic Mapping Study

Di Felice,

Paolone

2024

Journal of Computer Science

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In a previous article, we conducted a Systematic Mapping Study (SMS) devoted to identifying the open-source IoT platform that nowadays offers the most features as well as adequate documentation and which, therefore, is a useful middleware in the development of IoT applications. In light of the final findings of such a study, ThingsBoard was selected. The present paper reports on the findings of a subsequent mapping study. We queried the Scopus database looking for articles that mention ThingsBoard either in the Title, in the Abstract, or among the authors' Keywords. 55 items were retrieved and carefully read. At the end of this stage, we were able to answer the following research questions: Are there available studies mentioning ThingsBoard? In which ambits? What is the role of ThingsBoard in the studies where it is mentioned? What are the gaps in current research and the implications for future research? The study goals are general, so the final findings might be of interest to IoT professionals, as well as to scholars. In detail, the SMS provides insights into the breadth of usage and the domains where ThingsBoard has been applied successfully, indicating its suitability and potential for a wide range of IoT-related projects. Moreover, a few gaps to be filled with further research have emerged.

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Section: Resultsmentioning

confidence: 99%

Papers Mentioning Things Board: A Systematic Mapping Study

Di Felice,

Paolone

2024

Journal of Computer Science

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“…Online orders create opportunities for better management of production and inventory. Some authors believe that the main advantage of IoT is inventory management and supply chain management over precise product tracking and locating [28]. The hands-on IoT applications enable the following improvements:…”

Section: Electronic Commerce In the Iot Environmentmentioning

confidence: 99%

The Future of Electronic Commerce in the IoT Environment

Lazić,

Milić,

Vukmirović

2024

JTAER

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The Internet of Things (IoT) was born from the fusion of virtual and physical space and became the initiator of many scientific fields. Economic sustainability is the key to further development and progress. To keep up with the changes, it is necessary to adapt economic models and concepts to meet the requirements of future smart environments. Today, the need for electronic commerce (e-commerce) has become an economic priority during the transition between Industry 4.0 and Industry 5.0. Unlike mass production in Industry 4.0, customized production in Industry 5.0 should gain additional benefits in vertical management and decision-making concepts. The authors’ research is focused on e-commerce in a three-layer vertical IoT environment. The vertical IoT concept is composed of edge, fog, and cloud layers. Given the ubiquity of artificial intelligence in data processing, economic analysis, and predictions, this paper presents a few state-of-the-art machine learning (ML) algorithms facilitating the transition from a flat to a vertical e-commerce concept. The authors also propose hands-on ML algorithms for a few e-commerce types: consumer–consumer and consumer–company–consumer relationships. These algorithms are mainly composed of convolutional neural networks (CNNs), natural language understanding (NLU), sequential pattern mining (SPM), reinforcement learning (RL for agent training), algorithms for clicking on the item prediction, consumer behavior learning, etc. All presented concepts, algorithms, and models are described in detail.

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Quantitative Analysis of Urban Spatial Morphology Based on GIS Regionalization and Spatial Syntax

Chen

Liu

2022

J Indian Soc Remote Sens

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Internet of Things for Electronic Markets

Cited by 8 publications

References 10 publications

Papers Mentioning Things Board: A Systematic Mapping Study

Papers Mentioning Things Board: A Systematic Mapping Study

The Future of Electronic Commerce in the IoT Environment

Quantitative Analysis of Urban Spatial Morphology Based on GIS Regionalization and Spatial Syntax

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