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Evaluating IoT Cloud Platforms in the Context of Smart Buildings

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There are hundreds of Internet of Things (IoT) cloud platforms available to commercial smart buildings today, and that number is growing. Each platform has its strengths and weaknesses, each suited to different types of building with different objectives and IoT strategies. Property owners and managers are faced with the challenging task of selecting the right IoT cloud platform for their unique facilities with no obvious guidelines or means of comparison. One recent paper from a student at Malmö University proposes an innovative evaluation system to help solve the issue.

For many smart building buyers and decision-makers, the choice of cloud platform comes down to cost. Two years ago Edua Eszter Kalmar et al. conducted an investigation of different IoT cloud service providers pricing models. The paper focuses on four providers; Microsoft, IBM, Amazon, and Oracle. It used a survey as well as a cost comparison calculation tool and a test implementation to conclude that based on the number of devices, amount of messages and data used some providers cost less than others. While cost is an important factor in such decisions and a significant differentiator between cloud platform vendors, the best option cannot be found with cost evaluation alone.

A year earlier, in 2016, another paper ‘Selecting the right IoT Cloud Platform’ by Pankaj Ganguly sought to address the problem that there exists no list of requirements and related best practice of IoT cloud platforms. Based on the functional aspects of IoT cloud platforms, Ganguly developed a selection basis that can be used to compare IoT cloud platforms for application protocol, analytics, application support, and security. While the features of each cloud platform are fundamental to the decision on which to buy, this kind of evalution often lacks consideration of the platform’s implementation procedure.

In 2017, Tacklim Lee et al. presented a design and implementation of an intelligent, connected HVAC system that provides personalized settings for the users. Run on a Raspberry PI3, the researchers could remotely monitor the system to better assess the IoT cloud platform implementation process, providing valuable results but no comparison with other platforms. This built on a similar 2015 project by Enrique Carillo et al. who also developed, implemented and examined an IoT framework for cloud computing.

These studies have helped develop our understanding of IoT cloud platforms, their features, implementation processes, and cost, creating a body of information that could be used to select the most appropriate service provider. However, there is still a significant lack of technical understanding on the buyers’ side of the cloud service – smart building relationship. A method of comparison is needed that factors in cost, service, and implementation, then provides straightforward results that decision-makers can apply to their unique buildings.

A 2018 thesis by Gustaf Bohlin and Anton Hellbe at the University of Malmö was recently published and shows the makings of a potential evaluation process that could address the issue. The paper titled Evaluating IoT Cloud Platforms in the Context of Smart Buildings implements the same functionality on two cloud platforms (AWS and Azure) to compare a multitude of features and ease of implementation. A scoring system was developed that, if expanded, could act as a buyers’ guide to finding the ideal IoT cloud platform.

“To evaluate the IoT cloud platforms a common smart building scenario is realized by implementing a prototype using two different IoT cloud platforms. The development process makes it possible to evaluate how well the platforms support the development of the system that the scenario describes. The evaluation is based on information and experience from the process of developing the system using the IoT cloud platforms,” explained the paper. “The evaluation can be used as guidance when selecting IoT cloud platform for an IoT solution intended for a smart building.”

While there is no doubt that the scope of this study is too small to be certain of its effectiveness on a market-wide scale, it does present an efficient and functional system of comparison that could be scaled up to provide buyers a guide for IoT cloud platforms in smart buildings.

At the very least, this paper serves to highlight the complex issue of IoT cloud platform selection and the lack of proper guidance tools for building owners and managers to call upon. By empowering the buyer to identify the right service for their unique demands we create more successful smart building projects, giving a boost to the sector as a whole.

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