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 (22)
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..
DPISVM: A Dynamic Planar One-Class Support Vector Machine for Internet of Things Environment
Alistair Shilton, Sutharshan Rajasegarar, Christopher Leckie, Marimuthu Palaniswami
The Internet of Things realisations, such as smart city applications, generates a vast amount of data, and detecting emerging anom..
Ellipsoidal neighbourhood outlier factor for distributed anomaly detection in resource constrained networks
Sutharshan Rajasegarar, Alexander Gluhak, Muhammad Ali Imran, Michele Nati, Masud Moshtaghi, Christopher Leckie, Marimuthu Palaniswami
Anomaly detection in resource constrained wireless networks is an important challenge for tasks such as intrusion detection, quali..
High-Resolution Monitoring of Atmospheric Pollutants Using a System of Low-Cost Sensors
Sutharshan Rajasegarar, Timothy C Havens, Shanika Karunasekera, Christopher Leckie, James C Bezdek, Milan Jamriska, Ajith Gunatilaka, Alex Skvortsov, Marimuthu Palaniswami
Increased levels of particulate matter (PM) in the atmosphere have contributed to an increase in mortality and morbidity in commun..
High Resolution Spatio-temporal Monitoring of Air Pollutants Using Wireless Sensor Networks
Sutharshan Rajasegarar, Peng Zhang, Yang Zhou, Shanika Karunasekera, Christopher Leckie, Marimuthu Palaniswami
Atmospheric pollutants, such as gases and particu-late matters (PM) pose a threat to human health. In particular, there has been a..
Profiling spatial and temporal behaviour in sensor networks: A case study in energy monitoring
L RASHIDI, S Rajasegarar, CA Leckie, M Nati, A Gluhak, MA Imran, MS Palaniswami
Wireless sensor networks (WSNs) provide a cost-effective platform for monitoring phenomena of interest at fine spatial and tempora..
Smart Car Parking: Temporal Clustering and Anomaly Detection in Urban Car Parking
Yanxu Zheng, Sutharshan Rajasegarar, Christopher Leckie, Marimuthu Palaniswami
A major challenge for modern cities is how to maximise the productivity and reliability of urban infrastructure, such as minimisin..
A Pilot Study of Urban Noise Monitoring Architecture Using Wireless Sensor Networks
Jayavardhana Gubbi, Slaven Marusic, Aravinda S Rao, Yee Wei Law, Marimuthu Palaniswami
Internet of Things (IoT) is denned as interconnection of sensing and actuating devices providing the ability to share information ..
clusiVAT: A Mixed Visual/Numerical Clustering Algorithm for Big Data
Dheeraj Kumar, Marimuthu Palaniswami, Sutharshan Rajasegarar, Christopher Leckie, James C Bezdek, Timothy C Havens
Recent algorithmic and computational improvements have reduced the time it takes to build a minimal spanning tree (MST) for big da..