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Uncertainty in Ontology Approach

Ontology is the most widely used tool to integrate semantic into activity recognition. However, besides lack of temporal reasoning, ontology cannot deal with uncertainty [1]. Diaz et al. proposed a fuzzy ontology to solve this limitation. But, fuzzy approach allows more precise knowledge representation rather than deciding among multiple hypotheses and having a more coherent […]

Why dynamic sliding window technique is necessary in activity recognition?

Window size in (acceleration) signal segmentation for activity classification is important because it needs to capture necessary characteristics of the signals. Various sizes of window have been used in previous works without stating a specific reason. A window size is selected based on past experiments and hardware limitations. Majority of approaches used window size in […]

Sensor constraints and issues

Wilson and Atkeson [1] discussed several constraints and issues of sensors used in activity recognition system. The two main factors are sensor cost and sensor acceptance. Cameras and microphone are not suitable because inhabitant would feel uncomfortable living in the house. RF tags, badge, beacon or marker type of sensors including any wearable sensors potentially […]

Evaluation of accelerometer based multi-sensor versus single-sensor activity recognition systems

The paper describes the comparison of activity recognition system consisting of a single accelerometer sensor and multiple accelerometer sensors. The paper also presented the influence of sampling rate towards recognition accuracies, most widely used features in this research area and the time take to calculate them, and comparison between classifiers in activity recognition. The result […]

Features Extraction

Ravi et al. extracted features from raw data using a window size of 256 samples with 128 overlapping between consecutive windows. Sampling rate used is 50Hz which equivalent to 5.12s for each window. The calculated features are mean, standard deviation, energy and correlation. A single triaxial accelerometer was worn near the pelvic region in the […]

Window Segmentation Techniques

Preece et al. explained windowing techniques are used in most activity classification researches. In real-time applications, windows are defined concurrently with data collection. There are three different windowing techniques which are sliding windows, event-defined windows and activity-defined windows. The sliding window technique divided signals into fixed length (window) with no inter-window gap. The range of […]

Body Area Sensor Networks: Requirements, Operations, and Challenges

B. Johny and A. Anpalagan suggested health-care monitoring challenges can be tackled by interfacing sensors and actuators which form body area networks (BANs) with the human body together with the support of wireless technology and mobile and cloud computing [1]. Three stages of health-care monitoring system have been defined, which are sensors, data hub and […]

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, […]

Class of physical activities

Physical activities can be classified into dynamic, static and postural transition. Activities that are characterized by large movements such as walking and running are classified as dynamic activity, while static activity is defined by activities that involve small movement such as sitting, lying down and standing. Postural transitions is the movements that change from one […]

KCAR: A knowledge-driven approach for concurrent activity recognition

Ye et al. proposed a concurrent activity recognition technique by analyzing real-time input sensor events to determine their semantic dissimilarity to segment a continuous sensor sequence into fragments, which a fragment corresponds to one ongoing activity [1]. Sensor events is defined as a function with three parameters, each of which refers to reported time of […]