AI Article Synopsis
- The Internet of Things (IoT) is rapidly growing, leading to an increasing number of IoT data sources that require effective search and integration mechanisms.
- The paper introduces IoTCrawler, a system designed to connect various IoT solutions for better interoperability and to address data fragmentation, featuring a layered approach for crawling, indexing, and searching data.
- The framework meets essential requirements for IoT data searching and is validated through real-world use cases that demonstrate its practical applicability and flexibility for different scenarios.
Article Abstract
Due to the rapid development of the Internet of Things (IoT) and consequently, the availability of more and more IoT data sources, mechanisms for searching and integrating IoT data sources become essential to leverage all relevant data for improving processes and services. This paper presents the IoT search framework IoTCrawler. The IoTCrawler framework is not only another IoT framework, it is a system of systems which connects existing solutions to offer interoperability and to overcome data fragmentation. In addition to its domain-independent design, IoTCrawler features a layered approach, offering solutions for crawling, indexing and searching IoT data sources, while ensuring privacy and security, adaptivity and reliability. The concept is proven by addressing a list of requirements defined for searching the IoT and an extensive evaluation. In addition, real world use cases showcase the applicability of the framework and provide examples of how it can be instantiated for new scenarios.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7956704 | PMC |
| http://dx.doi.org/10.3390/s21051559 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!