The role of prediction algorithms in the MavHome smart home architecture

By Sajal K. Das, Diane Joyce Cook, A. Bhattacharya, E. O. Heierman, Tze-Yun Lin. IEEE wireless communications, 2002

372 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Transportation

View Paper: https://www.semanticscholar.org/paper/e4a4479db7b16f9b364fabb58bcdaf53812c6ad2

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Citations in the corpus

Predicting User-Cell Association in Cellular Networks from Tracked Data (2009, background): “Practically, on large networks the matrix A will become sparse and the J(2) factor can be replaced with J, a ∈ [1, 2), leading to O(t ·J · iterations) complexity.”
How smart are our environments? An updated look at the state of the art (2007, background): “The Neural Network House [54], the Intelligent Home [43], the House n [32] and the MavHome [17] [90] projects focus on the development of adaptive control of home environments by also anticipating the location, routes and activities of the inhabitants.”
Design and implementation of smart home energy management systems based on zigbee (2010, methodology): “For many sensor networks are a service this in the only traffic on the network, but even when there is other traffic, as in a home control system, there is often a central controller or TV, DVD that acts, for all intents and purposes, as an aggregator [4].”
Smart homes and their users: a systematic analysis and key challenges (2014, background): “Smart homes as intelligent and context-aware learning systems remove the need for any active user involvement at all by automating functions according to users’ revealed habits (e.g. [24, 52, 67]).”
Wireless Architectures for Heterogeneous Sensing in Smart Home Applications: Concepts and Real Implementation (2013, background): “On the other hand, it is worth observing that the actual trend of smart homes [50]–[52] is not only the capability to measure, control, and interconnect an unlimited number of sensors and actuators according to input commands, but also how to understand the habits and the behavior of inhabitants in…”
A Review of Smart Homes—Past, Present, and Future (2012, background): “The CASAS project has benefited from the aid of researchers who previously worked on the MavHome [15] smart home.”
Internet of Things: Architectures, Protocols, and Applications (2017, methodology): “Prediction algorithms are used to predict the sequence of events [76] in a home.”
Activity Recognition in the Home Using Simple and Ubiquitous Sensors (2004, background): “The SHIP algorithm matches the most recent sequence of events with collected histories of actions to predict inhabitant future actions [4].”