The 7th Workshop on Big Data Engineering and Analytics in Cyber-Physical Systems (BigEACPS'24)
A workshop co-located with the
2024 IEEE International Conference on Big Data (IEEE Big Data 2024)
The workshop will be held on
December 15 - 18, 2024, Washington DC, USA.
Deadline for Submission: October 10, 2024
Deadline for Submitting Papers Extended to : Nov. 9, 2024
Please submit papers in PDF via CyberChair - BigEACPS'24 Submission Site
The Internet of Things (IoT) and Cyber-Physical Systems (CPS) visions are to transform the social, business, enterprises, and our daily activities by incorporating the growing number of smart devices interconnected to the network. Smart devices, smart cars, smart homes, smart cities, and a smart world, in general, are becoming the reality. These paradigm shifts in socializing smart products over the Internet provide unique opportunities that are geared with new challenges. This transformation in the Internet technology haas introduced many grand challenges including scalability and robustness, dependencies, and architectural modeling, human factors and economics aspects, knowledge acquisition and Big Data, security, privacy, and trust issues. In particular, the amount of exchanged and collected data through IoT can be enormous that may introduce some other concerns including data management and maintenance, data heterogeneity, data security and privacy issues.
The goal of this workshop is to promote the state of the arts in scientific and practical research of the IoT and CPS in general, and Big Data and security challenges of these paradigms in specific. The workshop provides a forum for bringing together researchers from academia and practitioners from industry to present their research work and share their experience in the areas of IoT and CPS.
Authors are requested to submit papers reporting original and unpublished research results and experience report on above and other topics related to IoT and CPS.
The workshop also invites submission of research papers related to application of Generative AI and Large Language Models (LLMs) to problems pertinent to CPS, IoT, and Engineering application domains.