Contents & References of Energy awareness based on individual user activity on the mobile phone
List:
Abstract. 1
Chapter One: General Research
1-1-Definition. 3
1-2-Research limitation. 3
1-3-The importance of the subject. 4
1-4- Research objective. 4
1-5-Research method. 4
1-5-1- Steps to achieve activity detection in Android. 4
1-5-2- The reason for choosing Android programming to detect mobile activity. 4
1-6-steps of research. 5
1-7-Thesis structure. 5
Chapter Two: A review of research literature and research background
2-1-Objective. 8
2-2- Extracting energy from the environment to supply energy to mobile devices. 9
2-2-1-Overview of energy harvesting in mobile systems. 9
2-2-2-Principles of harvesting energy using human body heat. 11
2-2-3- Using the human body as a heat source for mobile sensors. 12
2-2-4-using TEGs in mobile devices. 14
2-3-Research history in getting to know mobile phone sensors and smartphones. 15
2-3-1-Sensors 15
2-3-2-Smartphones. 18
2-4-Research history of human activity detection by sensors 19
2-4-1-Definition and classification of human activities. 20
2-4-2-approaches to detect human activity. 24
2-4-2-1-video-based approach. 24
2-4-2-2-approach based on sensor environment. 24
2-4-2-3-approach based on wearable sensors. 24
2-4-3- approaches to modeling human activity. 25
2-4-3-1- feature extraction approach. 25
2-4-3-2-standard data and feature size reduction. 26
2-4-4-Activity detection algorithms. 26
2-4-4-1-clustering algorithms. 28
2-4-4-2-K-nn clustering algorithm. 29
2-4-4-3-ANN clustering algorithm. 29
2-4-4-4-SVM clustering algorithm. 29
2-4-4-5-Baysian clustering algorithm. 30
2-4-4-6-Naïve Bayes clustering algorithm. 30
2-4-4-7-Markov chain clustering algorithm. 30
2-4-4-8-HMM clustering algorithm. 30
2-4-4-9-Fuzzy Logic clustering algorithm. 31
2-4-5-challenges 32
2-4-5-1-complexity of activities 32
2-4-5-2-number of activities 32
2-4-5-3-type of activity. 32
2-4-5-4-Educational data requirements. 33
2-4-5-5-need for accuracy. 33
2-4-5-6-long-term and high-level activity. 33
2-4-6-sensor requirements. 34
2-4-7-location of sensors 34
2-4-8-real-time detection. 34
2-4-9-pattern of human activity. 35
2-4-10- A simple example of work on the detection of human activities. 37
2-5- History of research on activity detection in mobile phones. 38
2-6-Summary. 51
The third chapter. 57
Research tools. 57
Mechanism for detecting (detecting) user activity in computing devices. 57
The third chapter: Research implementation method
3-1-Introduction. 58
3-2- Introduction to Android programming. 58
3-2-1-Problems. 59
3-2-2-Applications 59
3-2-3-A simple example of revealing human activities in the home environment. 60
3-3- Display hierarchy. 61
3-4-Film detection. 62
3-5-sound events. 62
3-6-Characteristics of shape and color. 62
3-7-IE detection. 63
3-8- Detection of GF and GE. 63
3-9-Detecting human activities from behind obstacles using the animation of Doppler radar signals 63
3-10-Detecting through RFID. 64
3-11-Activity detection in Android. 65
3-12-Determining user activity in mobile (achievements, challenges, recommendations). 65
Chapter Four: Data Analysis
4-1-Introduction. 71
4-2-Data collection 71
4-3-Data generation 72
4-4-Program data collection. 74
4-5-sensor management. 75
4-6-Location management. 75
4-7-File management. 76
4-8-activity class. 76
4-9-Steps of implementing the program. 77
4-10- Feature extraction. 84
4-11-Activity identification. 87
Chapter Five: Conclusions and Suggestions
5-1-Summary. 90
5-2-Future work. 94
List of sources. 96
Appendix. 100
Source:
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