Name
Abstract | ||
|---|---|---|
In recent years, WSNs are garnering lot of interest from research community because of their unique characteristics and potential for enormous range of applications. Envision for new class of applications are being emerged such as human augmentation, enhancing social interaction etc. Misunderstanding or misinterpretation of behaviors from individuals leads to social conflicts. There are various theories that classify people into different personality types. Most of the existing theories rely on questionnaires, which is highly unreliable. Anyone can lead such theories in practice to incorrect classification intentionally or unintentionally. The objective of this research is to investigate existing solutions and propose a basic infrastructure for an automated context-aware psychological classification based on different parameters. The idea is to use wearable sensors to sense and measure various human body parameters (i.e. body temperature, blood pressure, perspiration, brain impulses etc) that coerce human psychological condition. The data collected from these parameters is transformed in to information, to determine personality type, mood and psychological condition of interacting parties. This information is shared among counterparts to better understand each other in order to avoid potential conflicting situations. We believe that it will help peoples understand each other, improve their quality of life and minimize possible conflicting situations. |
Year | Venue | Field |
|---|---|---|
2012 | CoRR | Data science,Social relation,Mood,Personality type,Wearable computer,Computer science,Social conflict,Artificial intelligence,Wireless sensor network,Distributed computing,Personality |
DocType | Volume | Citations |
Journal | abs/1212.5543 | 1 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Muhammad Imran | 1 | 35 | 6.58 |
| Halabi Hasbullah | 2 | 161 | 12.39 |
| Abas Md. Said | 3 | 84 | 8.17 |