A Comprehensive Evaluation of IoT Cloud Platforms: A Feature-Driven Review with a Decision-Making Tool

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Библиографические подробности
Опубликовано в::	Sensors vol. 25, no. 16 (2025), p. 5124-5182
Главный автор:	Panagou Ioannis Chrysovalantis
Другие авторы:	Katsoulis Stylianos, Nannos Evangelos, Zantalis Fotios, Koulouras Grigorios
Опубликовано:	MDPI AG
Предметы:	Smart cities Data processing Cost analysis Data analysis Connectivity User needs Edge computing Internet of Things Manuscripts Decision making Empowerment Comparative analysis
Online-ссылка:	Citation/Abstract Full Text + Graphics Full Text - PDF
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Описание
Краткий обзор:	The rapid proliferation of Internet of Things (IoT) devices has led to a growing ecosystem of Cloud Platforms designed to manage, process, and analyze IoT data. Selecting the optimal IoT Cloud Platform is a critical decision for businesses and developers, yet it presents a significant challenge due to the diverse range of features, pricing models, and architectural nuances. This manuscript presents a comprehensive, feature-driven review of twelve prominent IoT Cloud Platforms, including AWS IoT Core, IoT on Google Cloud Platform, and Microsoft Azure IoT Hub among others. We meticulously analyze each platform across nine key features: Security, Scalability and Performance, Interoperability, Data Analytics and AI/ML Integration, Edge Computing Support, Pricing Models and Cost-effectiveness, Developer Tools and SDK Support, Compliance and Standards, and Over-The-Air (OTA) Update Capabilities. For each feature, platforms are quantitatively scored (1–10) based on an in-depth assessment of their capabilities and offerings at the time of research. Recognizing the dynamic nature of this domain, we present our findings in a two-dimensional table to provide a clear comparative overview. Furthermore, to empower users in their decision-making process, we introduce a novel, web-based tool for evaluating IoT Cloud Platforms, called the “IoT Cloud Platforms Selector”. This interactive tool allows users to assign personalized weights to each feature, dynamically calculating and displaying weighted scores for each platform, thereby facilitating a tailored selection process. This research provides a valuable resource for researchers, practitioners, and organizations seeking to navigate the complex landscape of IoT Cloud Platforms.
ISSN:	1424-8220
DOI:	10.3390/s25165124
Источник:	Health & Medical Collection