Developing an Expert System for Hardware Selection in Internet of Things-Based System Design: Grey ITARA-COBRA Approach (With an Example in the Agricultural Domain)
Internet of Things (IoT) technology is rapidly transforming various industries. Advancements in production technologies have made it more affordable to produce suitable hardware to create IoT-based systems. This has resulted in a wide range of options available at reasonable prices. Having multiple...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
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| Series: | Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2078-2489/16/6/425 |
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| Summary: | Internet of Things (IoT) technology is rapidly transforming various industries. Advancements in production technologies have made it more affordable to produce suitable hardware to create IoT-based systems. This has resulted in a wide range of options available at reasonable prices. Having multiple options available gives designers creative freedom. However, having more options may confuse designers and make it more difficult to choose hardware that meets design needs. This paper presents an expert system for IoT-based system hardware selection. In the proposed approach, the hardware information and expert knowledge are stored in a database and a knowledge base. Users input their required specifications using a user interface, and then the system’s decision-making module constructs the decision matrix and eventually ranks the alternatives utilizing a hybrid ITARA-COBRA method. Due to the ambiguity in the data, grey numbers are used for decision-making. In the next step, an example of an agricultural IoT-based system design is applied to test the system. The proposed Grey ITARA method is compared with the Grey MEREC and Grey CRITIC methods, and given the use of the indifference threshold concept, it performs well. Moreover, its ability to handle unstructured, vague data is useful for using technical specifications and expert opinions in decision-making. |
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| ISSN: | 2078-2489 |