Mood Based Building Automation Using Fuzzy Petrinets

Year 2015, Volume: 6 Issue: 20, 51 - 64, 01.07.2015

Manuj Darbari Ruchi Davey Naveen Hemrajani

https://doi.org/10.5824/1309-1581.2015.3.004.x

Abstract

This paper deals with MOOD based building automation system. It categorises various aspects of MOOD and its relationship with dynamic setting of the environment. It uses Fuzzy Petrinets to fine tune the environment setting if it exists. Error and error Dot membership function based on Rule Matrix. Workflow is defined to generate the algorithm.

Keywords

MOOD Environment, Emotional Analysis, Fuzzy Petrinets.

Mood Based Building Automation Using Fuzzy Petrinets

Abstract

This paper deals with MOOD based building automation system. It categorises various aspects of MOOD and its relationship with dynamic setting of the environment. It uses Fuzzy Petrinets to fine tune the environment setting if it exists. Error and error Dot membership function based on Rule Matrix. Workflow is defined to generate the algorithm.

Keywords

MOOD Environment, Emotional Analysis, Fuzzy Petrinets.

References

• Ahmad, F., Darbari, M., & Asthana, R. (2015). Different Approaches of Soft Computing Techniques (Inference System) which are used in Clinical Decision Support System for Risk based Prioritization. Asian Journal of Computer and Information Systems, 3(1). Chicago
• Ahmad, S. S., Purohit, H., Mohammed, F. N., & Darbari, M. (2013). Information granules for medical infonomics. International Journal of Information and Operations Management Education, 5(3), 205-213.
• Berkovitz, L. D. (2013). Optimal control theory (Vol. 12). Springer Science & Business Media.
• Dang, T. H. H., Letellier-Zarshenas, S., & Duhaut, D. (2008). Comparison of recent architectures of emotions. In 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008.
• Darbari, M., & Asthana, R. (2013). Intelligent Urban Traffic Modeling Using Neuro-Fuzzy Petrinets. Scholars Press.
• Darbari, M., & Sahai, P. Article: Adaptive e-Learning Multi-Agent Systems with Swarm Intelligence. International Journal of Applied, 7, 16-20.Chicago
• Darbari, M., Ahmed, H., & Singh, V. K. (2011). Application of Fuzzy Automata Theory and Knowledge Based Neural Networks for Development of Basic Learning Model. Computer Technology and Application, Vol 2, (pp. 58-61).
• Darbari, M., Asthana, R., Ahmed, H., & Ahuja, N. J. (2011). Enhancing the capability of N-dimension self-organizing Petrinet using neuro-genetic approach. International Journal of Computer Science Issues (IJCSI), 8(3).
• Darbari, M., Karn, B., & Ahmad, H. (2008). Modeling Intelligent Transport System using OPAT: A Language To Transform Multi Agent System In Object Oriented Notation. In Proceedings of the International MultiConference of Engineers and Computer Scientists (Vol. 1).
• Darbari, M., Singh, V. K., Asthana, R., Prakash, S., & Kendra, D. (2010). N-Dimensional Self Organizing Petrinets for Urban Traffic Modeling. IJCSI.
• Darbari, M., Yagyasen, D., & Tiwari, A. (2015, January). Intelligent Traffic Monitoring Using Internet of Things (IoT) with Semantic Web. In Emerging ICT for Bridging the Future-Proceedings of the 49th Annual Convention of the Computer Society of India (CSI) Volume 1 (pp. 455-462). Springer International Publishing.
• Dhanda, N., Darbari, M., & Ahuja, N. J. (2012). Development of Multi Agent Activity Theory e- Learning (MATeL) Framework focusing on Indian Scenario. International Review on Computers and Software, 7(4).
• Han, J., Yun, J., Jang, J., & Park, K. R. (2010). User-friendly home automation based on 3D virtual world. Consumer Electronics, IEEE Transactions on, 56(3), 1843-1847.
• Liu, D., Lu, L., & Zhang, H. (2003, October). Automatic mood detection from acoustic music data. In ISMIR.
• Paiva, R. P. (2013). MOODetector: Automatic Music Emotion Recognition, PROMETEO.
• Prakash, S., & Darbari, M. (2012). ‘Quality & Popularity’Prediction Modeling of TV Programme through Fuzzy QFD Approach. Journal of Advances in Information Technology, 3(2), 77-90.
• Saastamoinen, H. (1995). “On the handling of exceptions in information systems”. Ph.D. thesis, University of Jyvaskyla, Finland.
• Saha, A., Kuzlu, M., & Pipattanasomporn, M. (2013, February). Demonstration of a home energy management system with smart thermostat control. In Innovative Smart Grid Technologies (ISGT), 2013 IEEE PES (pp. 1-8). IEEE.
• Sen, I., & Matolak, D. W. (2008). Vehicle–vehicle channel models for the 5-GHz band. Intelligent Transportation Systems, IEEE Transactions on, 9(2), 235-245.
• Sethi, S. P., & Thompson, G. L. (2000). What is Optimal Control Theory? (pp. 1-22). Springer US.
• Shukla, P. K., Darbari, M., Singh, V. K., & Tripathi, S. P. (2011). A Survey of Fuzzy Techniques in object oriented databases. International Journal of Scientific and Engineering Research, 2(11), 1-11.
• Thayer, R. E. (1989). The biopsychology of mood and arousal. Oxford University Press.
• Yagyasen, D., & Darbari, M. (2014). Application of Semantic Web and Petri Calculus in Changing Business Scenario. In Modern Trends and Techniques in Computer Science (pp. 517-528). Springer International Publishing.
• Yagyasen, D., Darbari, M., Shukla, P. K., & Singh, V. K. (2013). Diversity and convergence issues in evolutionary Multiobjective optimization: application to agriculture science. IERI Procedia, 5, 81-86.