Real Time Risk Monitoring in Fine-art with IoT Technology
Journal Title: Annals of Computer Science and Information Systems - Year 2018, Vol 17, Issue
Abstract
This work presents a bespoke system used to monitor inter-modal logistics within the fine arts industry. A custom IoT architecture provides end-to-end capabilities allowing continuous risk assessment during storage, handling, transport and exhibition. The system overcomes the challenges of implementing adaptive artificial intelligence systems, extra low latency and exceptional power efficiency within a fully integrated IoT architecture. The main contribution of this paper lies in the architecture that has been fully implemented and commercialized to international leading companies.
Authors and Affiliations
Vincenza Carchiolo, Mark Phillip Loria, Marco Toja, Michele Malgeri
Automatic Assessment of Student Understanding Level using Virtual Reality
The improvement of the efficiency in teaching re- quires knowing the understanding level of each student. However, it is difficult due to limited time in a class. We propose a Virtual Reality (VR) space imposing assignme...
Reliability Modeling of OSS Systems based on Innovation-Diffusion Theory and Imperfect Debugging
Open Source Software (OSS) has obtained widespread popularity in last few decades due to the exceptional contribution of some well established ones like Apache, Android, MySQL, LibreOffice, Linux etc. not only in the fie...
Kestrel-based Search Algorithm (KSA) and Long Short Term Memory (LSTM) Network for feature selection in classification of high-dimensional bioinformatics datasets
Although deep learning methods have been applied to the selection of features in the classification problem, current methods of learning parameters to be used in the classification approach can vary in accuracy at each t...
Importance of Text Data Preprocessing & Implementation in RapidMiner
Data preparation is an important phase before applying any machine learning algorithms. Same with the text data before applying any machine learning algorithm on text data, it requires data preparation. The data preparat...
Ranking Rough Sets in Pawlak Approximation Spaces
By the cardinality of finite sets, interval numbers can be assigned to rough sets which are represented by nested sets. Borrowing two different comparison methods from Multiple Attribute Decision Making analysis, rough s...