Creating a Smart City through Internet of Things
Grant number: LP120100529 | Funding period: 2012 - 2017
This project will deliver smart new ways of urban monitoring using ubiquitous sensing and data analysis for city management and sustainability. It will deliver researcher training, global clientele for local technology and a platform for local industry growth.
Related publications (10)
Ensemble Fuzzy Clustering Using Cumulative Aggregation on Random Projections
Punit Rathore, James C Bezdek, Sarah M Erfani, Sutharshan Rajasegarar, Marimuthu Palaniswami
Random projection is a popular method for dimensionality reduction due to its simplicity and efficiency. In the past few years, ra..
Real-Time Urban Microclimate Analysis Using Internet of Things
Punit Rathore, Aravinda S Rao, Sutharshan Rajasegarar, Elena Vanz, Jayavardhana Gubbi, Marimuthu Palaniswami
Real-time environment monitoring and analysis is an important research area of Internet of Things (IoT). Understanding the behavio..
Maximum Entropy-Based Auto Drift Correction Using High-and Low-Precision Sensors
Punit Rathore, Dheeraj Kumar, Sutharshan Rajasegarar, Marimuthu Palaniswami
With the advancement in the Internet of Things (IoT) technologies, variety of sensors including inexpensive, low-precision sensors..
A visual-numeric approach to clustering and anomaly detection for trajectory data
Dheeraj Kumar, James C Bezdek, Sutharshan Rajasegarar, Christopher Leckie, Marimuthu Palaniswami
This paper proposes a novel application of Visual Assessment of Tendency (VAT)-based hierarchical clustering algorithms (VAT, iVAT..
Adaptive Cluster Tendency Visualization and Anomaly Detection for Streaming Data
Dheeraj Kumar, James C Bezdek, Sutharshan Rajasegarar, Marimuthu Palaniswami, Christopher Leckie, Jeffrey Chan, Jayavardhana Gubbi
The growth in pervasive network infrastructure called the Internet of Things (IoT) enables a wide range of physical objects and en..
A Hybrid Approach to Clustering in Big Data
Dheeraj Kumar, James C Bezdek, Marimuthu Palaniswami, Sutharshan Rajasegarar, Christopher Leckie, Timothy Craig Havens
Clustering of big data has received much attention recently. In this paper, we present a new clusiVAT algorithm and compare it wit..
High-Dimensional and Large-Scale Anomaly Detection using a Linear One-Class SVM with Deep Learning
S MONAZAM ERFANI, S Rajasegarar, S Karunasekera, C Leckie
High-dimensional problem domains pose significant challenges for anomaly detection. The presence of irrelevant features can concea..