000			01904nam a22002057a 4500
003			OSt
005			20220107122852.0
008			190705b xxu||||| |||| 00| 0 eng d
040			_cIIITMK
100			_aDevika B Kumar (92217009) _916117
245			_aDaily human activities recognition using heterogeneous sensors from smart devices
300			_aMSC DA 2017-2019
500			_aPhysical activities play a very important role in our physical and mental well-being. The lack of physical activities can negatively aect our wellbeing. Though people know the importance of physical activities, still they need regular motivational feedback to remain active in their daily life. In order to give them proper motivational feedback, we need to recognize their physical activates rst (in our case, the main target group is knowledge workers). Therefore, this research is about recognizing human context (condition, activity and situation etc.) using heterogeneous sensors. If recognized reliably, this context can enable novel well-being applications in dierent elds, for example, healthcare. As a rst step to achieve this goal, we recognize some physical activities using smartphone sensors like accelerometer, gyroscope, and magnetometer. Moreover, we are simulating a smartphone on a wrist position as a smart watch and want to see the possibilities of activity recognition with upcoming smart watches. We want to reliably recognize physical activities using heterogeneous sensor information, that may be incomplete or unreliable. We are currently working on improving the existing work by investigating and solving the open challenges in activity recognition using smartphone sensors.
502			_bMSC DA _c2017-2019 _dINT _eDr T K Manoj Kumar
650			_aRANDOM FOREST _916118
650			_aDECISION TREE _916119
650			_aNAIVE BAYES _916120
650			_aMACHINE LEARNING _916121
942			_2ddc _cPR
999			_c6556 _d6556