In contrast to supervised learning, unsupervised learning deals with inputs only . This dataset is called unlabelled dataset. Since, we are dealing with inputs only the aim of unsupervised learning is to uncover the latent structure in data. For example, we want to know how many groups (classes) can we make out of the data?…
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Focus areas of context-aware research
1. Activity recognition [1][4][5][8][13] 2. Specific activity [2] 3. System [3][9][11] 4. Energy management [6][15] 5. Augmentation [7] 6. Data intepretation/Processing [10][19] 7. Reasoning [1][12][16][17][18] 8. Modeling [14] [1] F. Zhou, J. Jiao, S. Chen, and D. Zhang, ‘A Case-Driven Ambient Intelligence System for Elderly in-Home Assistance Applications’, IEEE Transactions on Systems, Man, and Cybernetics,…
Context Modeling
One of the method of context modeling is by using ontologies. Ontologies facilitate structuring data and representing knowledge. It define a given domain in a graph structure which contains concepts present in the modelled domain, the relationship between concepts and potentially classification axioms which specify generic knowledge about the domain. The ontologies is exploited by…
Input for Context Aware System
Not every input to context aware system is information. It could be raw data. For example, location and temperature. Temperature is a raw data from temperature sensor and location is an information which generated by processing raw data from accelerometer, gyrosensor? and magnetometer?. Both values could be inputs to context aware system. Therefore there is…
Taxonomy of Context Aware IoT middleware solution
Context acquisition -> Context Modeling -> Context Reasoning -> Context Distribution
Context Aware Computing
A survey has been conducted by Perera et al. [1] on the functionalities of Middleware for IoT. Functionalities that have been considered are device management, interoperation, platform portability, context-awareness, and security and privacy. The survey shows majority of Middleware solution do not provide context-awareness functionality. According to Abowd and Dey [2], context is defined as…
Sensors for Context Aware System
There are two categories of sensors for healthcare application. The first category is called ambient sensors. Ambient sensor is used to monitor the general activity patterns based on spatial and temporal information processing. Examples of ambient sensors are fall detectors, door monitors, bed alerts, pressure mats, smoke and heat alarms etc. More recent works on…
Middleware for Networked Embedded Systems for IOT
Amount of different devices (sensor nodes) interacting in an IOT environment is big. These devices must be able to connect to each other despite their different network technologies. Furthermore, the devices also require service discovery procedures as well as means to enforce semantic compatibility between devices. These requirement create a demand for a software layer…
Wireless Sensor Networks (WSN)
Wireless sensor networks is a wireless network that consists of spatially distributed autonomous devices using sensors to monitor environment condition such as temperature, humidity, sound, image and etc.
The “Internet of Things”
Internet of Things refers to the virtual interconnection of identifiable objects which is like the Internet-structure. The identifiable objects (nodes) could be any devices around us that contains embedded technology which can sense and communicate with its external environment. This interconnection forms a network of billion physical nodes, and by the year of 2020 it…