Title | Towards Swarm Intelligence Architectural Patterns: an IoT-Big Data-AI-Blockchain convergence perspective |
Publication Type | Conference Paper |
Year of Publication | 2019 |
Authors | Hibti, Meryem, Baïna, Karim, Benatallah, Boualem |
Conference Name | Proceedings of the 4th International Conference on Big Data and Internet of Things |
Publisher | Association for Computing Machinery |
Conference Location | Rabat, Morocco |
ISBN Number | 978-1-4503-7240-4 |
Keywords | AI, Big Data analytics, composability, compositionality, decision making, IoT, patterns, pubcrawl, swarm intelligence |
Abstract | The Internet of Things (IoT) is exploding. It is made up of billions of smart devices -from minuscule chips to mammoth machines - that use wireless technology to talk to each other (and to us). IoT infrastructures can vary from instrumented connected devices providing data externally to smart, and autonomous systems. To accompany data explosion resulting, among others, from IoT, Big data analytics processes examine large data sets to uncover hidden patterns, unknown correlations between collected events, either at a very technical level (incident/anomaly detection, predictive maintenance) or at business level (customer preferences, market trends, revenue opportunities) to provide improved operational efficiency, better customer service, competitive advantages over rival organizations, etc. In order to capitalize business value of the data generated by IoT sensors, IoT, Big Data Analytics/IA need to meet in the middle. One critical use case for IoT is to warn organizations when a product or service is at risk. The aim of this paper is to present a first proposal of IoT-Big Data-IA architectural patterns catalogues with a Blockchain implementation perspective in seek of design methodologies artifacts. |
URL | https://doi.org/10.1145/3372938.3372962 |
DOI | 10.1145/3372938.3372962 |
Citation Key | hibti_towards_2019 |