A Survey on IoT Programming Platforms: A Business-Domain Experts Perspective

IF 23.8 1区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS

ACM Computing Surveys Pub Date : 2024-10-14 DOI:10.1145/3699954

Fatma-Zohra Hannou, Maxime Lefrançois, Pierre Jouvelot, Victor Charpenay, Antoine Zimmermann

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引用次数: 0

Abstract

The vast growth and digitalization potential offered by the Internet of Things (IoT) is hindered by substantial barriers in accessibility, interoperability, and complexity, mainly affecting small organizations and non-technical entities. This survey paper provides a detailed overview of the landscape of IoT programming platforms, focusing specifically on the development support they offer for varying end-user profiles, ranging from developers with IoT expertise to business experts willing to take advantage of IoT solutions to automate their organization processes. The survey examines a range of IoT platforms, classified according to their programming approach between general-purpose programming solutions, model-driven programming, mashups and end-user programming. Necessary IoT and programming backgrounds are described to empower non-technical readers with a comprehensive field summary. In addition, the paper compares the features of the most representative platforms and provides decision insights and guidelines to support end-users in selecting appropriate IoT platforms for their use cases. This work contributes to narrowing the knowledge gap between IoT specialists and end users, breaking accessibility barriers and further promoting the integration of IoT technologies in various domains.

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物联网编程平台调查：业务领域专家视角

物联网（IoT）提供了巨大的增长和数字化潜力，但在可访问性、互操作性和复杂性方面却存在巨大障碍，主要影响到小型组织和非技术实体。本调查报告详细概述了物联网编程平台的现状，特别关注这些平台为不同最终用户提供的开发支持，这些用户既包括具备物联网专业知识的开发人员，也包括愿意利用物联网解决方案实现组织流程自动化的业务专家。调查研究了一系列物联网平台，并根据其编程方法在通用编程解决方案、模型驱动编程、混搭和最终用户编程之间进行了分类。本文介绍了必要的物联网和编程背景，为非专业读者提供了全面的领域总结。此外，本文还对最具代表性的平台的功能进行了比较，并提供了决策见解和指南，以支持最终用户为其使用案例选择合适的物联网平台。这项工作有助于缩小物联网专家与终端用户之间的知识差距，打破无障碍障碍，进一步促进物联网技术在各个领域的整合。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

ACM Computing Surveys 工程技术-计算机：理论方法

CiteScore

33.20

自引率

0.60%

发文量

372

审稿时长

12 months

期刊介绍： ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.