City Data Fusion: Sensor Data Fusion in the Internet of Things

By Meisong Wang, Charith Perera, Prem Prakash Jayaraman, Miranda Zhang, P. Strazdins, R. Ranjan. 2015

92 citations recorded by the source corpus.

Internet of Things IoT has gained substantial attention recently and play a significant role in smart city application deployments. A number of such smart city applications depend on sensor fusion capabilities in the cloud from diverse data sources. The authors introduce the concept of IoT and present in detail ten different parameters that govern our sensor data fusion evaluation framework. They then evaluate the current state-of-the art in sensor data fusion against our sensor data fusion framework. The authors' main goal is to examine and survey different sensor data fusion research efforts based on our evaluation framework. The major open research issues related to sensor data fusion are also presented.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Water Science and Technology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Billy Pik Lik Lau
2. Wenxiu Ding
3. Chau Yuen
4. Zheng Yan
5. Adarsh Kumar
6. Yuren Zhou
7. Meng Zhang
8. U-Xuan Tan

In Computer Vision and Pattern Recognition

1. Chau Yuen
2. Zheng Yan
3. Laurence Tianruo Yang
4. Wenxiu Ding
5. Xuyang Jing

Citations in the corpus

• A survey on data fusion in internet of things: Towards secure and privacy-preserving fusion (2019, background): “Objectives and Topics Limitation [15] Focus on data fusion algorithms and theories Not highly related to IoT data fusion [16] Focus on data fusion methods in specific IoT environments Ignore privacy and security in IoT data fusion [17] Classification of data fusion methods: stage-based methods, feat”
• A survey of data fusion in smart city applications (2019, background): “Wang et al. [20] Proposes an IoT architecture concept to survey on the different sensor data fusion techniques and also provides an overall view on their evaluation framework.”
• An Overview of IoT Sensor Data Processing, Fusion, and Analysis Techniques (2020, methodology): “Knowledge-based methods include artificial neural networks, fuzzy logic, genetic algorithms, etc. [55,56].”