Data fusion in the internet of data

Abstract

This special issue collates a selection of representative research articles that were primarily presented at the 2nd International Workshop on Data Mining on Internet of Things (IoT) Systems. This annual workshop brings together researchers and practitioners from both academia and industry who are working on data mining approaches on the IoT with applications in the Smart City framework and in the Cultural Heritage research domain in order to promote an exchange of ideas, discuss future collaborations, and develop new research directions.The Internet of Things envisages a plethora of heterogeneous objects interacting with the physical environments. It can be foreseen that IoT applications will raise the scale of data to an unprecedented level. Collecting, analyzing, and correlating data from different resources is a key role to drive smart interactions between actors of IoT environments.In this scenario, the Internet of Data (IoD) represents a concept of network composed by data entities coming from the Interne of Things (IoT).The IoD can be considered an extension of the IoT into the digital world, since the amount of data being collected is staggering. The opportunities created by IoD have the potential to be infinite. The IoD presents an ambitious purpose, ie, organizing the data to be interconnected as a network in order to infer useful information for data analysis and creates useful, customized, and location-based services.The scope of this special issue is broad and is representative of the multidisciplinary nature of the Internet of Data research field.Zheng et al 1 propose a term representation framework for four different features, ie, temporal feature, geographical feature, term co-occurrence, and hashtag. The framework deals with a series of attribution definition to detect topics on a Twitter dataset and confirm the effectiveness of LTDMF.The authors have also deeply analyze the importance of different features in topic detection.Kumar et al 2 present an efficient and secure time-limited hierarchical key assignment scheme key management suitable for data outsourcing scenario. They compare the proposed scheme with other recent similar schemes with respect to the cost of static and dynamic operations.The obtained results show that with similar unit private storage cost; the proposed scheme manages to reduce the key generation cost at the data owner and key derivation cost by each user.Wi and Tsai 3 propose a system to analyze at-home behavior and physiological indices of the elderly people. The design concepts for software and hardware equipment emphasize the following features: (1) low-cost sensor devices, (2) user-friendly interface for the wearable device, (3) easy installation for the equipment, and (4) low-power consumption for the wearable device.Experiment results show that the system simulation proves the algorithm to be feasible.Malik et al 4 discuss a data transformation methodology for geo-related semantic annotation and the importance of reducing the response time of investigation and offe...

Spatial Characteristics of Sports Tourism Destination System Based on Data Fusion and Data Mining

“…Piccialli worked on applying data mining methods for IoT in the field of smart city framework and cultural heritage research to facilitate the exchange of ideas, discuss future collaborations, and develop new research directions. It is foreseeable that the application of the Internet of ings will increase the scale of data to an unprecedented level [6]. Sene described a formalization of the medical decision-making process under uncertainty based on conditional preferences, evidence theory, and exploiting high-utility patterns in data mining.…”

Victim detection platform in IoT paradigm

“…Over the past few years, IoT has attracted much attention from both industrial and research communities, and it represents a network consisting of physical objects such as sensors, mobiles, buildings and vehicles in which software and electronics are embedded to connect with Internet and to enable collecting and exchanging data between them 1,2 . Although IoT techniques cannot directly stop disasters from happening, but as the complementary technology to a poor infrastructure, it is very useful for disaster management, such as disaster predictions, early warning systems and rescue operations 3,4 …”