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Internet of Things (IoT): A vision, architectural elements, and future directions
An Information Framework for Creating a Smart City Through Internet of Things
- Jiong Jin, J. Gubbi, S. Marusic, M. Palaniswami
- Computer ScienceIEEE Internet of Things Journal
- 9 January 2014
A framework for the realization of smart cities through the Internet of Things (IoT), which encompasses the complete urban information system, from the sensory level and networking support structure through to data management and Cloud-based integration of respective systems and services, and forms a transformational part of the existing cyber-physical system.
Smoke detection in video using wavelets and support vector machines
Sensor Network Implementation Challenges in The Great Barrier Reef Marine Environment
This paper analyses sensor network deployment issues in relation to harsh marine environment and proposes to use Microsoft SensorMap to provide a platform to disseminate the information collected from weather stations and sensor networks to the Worldwide coral reef research community and also to the worldwide sensor networks research community.
A neural network based adaptive non-linear lossless predictive coding technique
The results presented here also incorporate an arithmetic coding scheme, producing results which are better than CALIC and comparable to TMW, the state of the art lossless compression in the literature, showing that near-optimal results can be obtained with the fundamental concept of adaptive training.
Demand Response Architectures and Load Management Algorithms for Energy-Efficient Power Grids: A Survey
- Yee Wei Law, T. Alpcan, V. Lee, A. Lo, S. Marusic, M. Palaniswami
- EngineeringSeventh International Conference on Knowledge…
- 8 November 2012
DR architectures are surveyed, which are ICT architectures for enabling DR programs as well as load management, and load management solutions for responding to DR programs, in the form of load reduction and load shifting algorithms.
Crowd Event Detection on Optical Flow Manifolds
- A. S. Rao, J. Gubbi, S. Marusic, M. Palaniswami
- Computer ScienceIEEE Transactions on Cybernetics
- 1 July 2016
The proposed approach to detect the events in a probabilistic framework for automatically interpreting the visual crowd behavior is shown to produce the best results in merging, splitting, and dispersion events, and comparable results in walking, running, and evacuation events when compared with other methods.
Estimation of crowd density by clustering motion cues
The proposed approach to estimate crowd density using motion cues and hierarchical clustering incorporates optical flow for motion estimation, contour analysis for crowd silhouette detection, and clustering to derive the crowd density.
Crowd density estimation based on optical flow and hierarchical clustering
- A. S. Rao, J. Gubbi, S. Marusic, P. Stanley, M. Palaniswami
- Computer ScienceInternational Conference on Advances in Computing…
- 21 October 2013
A block-based dense optical flow with spatial and temporal filtering is used to obtain velocities in order to infer the locations of objects in crowded scenarios and a hierarchical clustering is employed to cluster the objects based on Euclidean distance metric.