Education System re-engineering with AI (artificial intelligence) for Quality Im-provements with proposed model

Abstract

Re-engineering (RE) of existing educational institutions (EI) with adoption of latest technology trends (LTT) in form of artificial intelligence (AI) can be great effective in term of quality systems. Increase in student’s strength in class and terrorist attacks on EI urged us to introduce such approach that can assure education quality. Class monitoring with heavy strength always remain major issue for teacher during lecture delivery. In this paper, we implemented reengineering using artificial intelligence based two theories of 1) Multi-face recognition (MFR) system 2) Facial expression recognition (FER) system. Both of these theories supported by intelligent techniques as principal component analysis (PCA), discrete wavelet transform (DWT) and k-nearest neighbor (KNN). After implementation of these intelligent techniques student’s attentiveness will increase. Our developed system can detect expressions like happiness, repulsion, fear, anger, and confusion. Student’s attentiveness score will be displayed on screen. Teacher can interpret on the basis of attentiveness %age. System decision making can be helpful for class continuity or short break. This system is also an application of an expert system (ES) and knowledge base system (KBS) for educational quality assurance. A similar monitoring system was imposed in china with Hikvision Digital Technology. Predations results proved monitoring can be best way for education quality.
  • Referencias
  • Cómo citar
  • Del mismo autor
  • Métricas
Hu, L. and Nooshabadi, S. –Massive parallelization of approximate nearest neighbor search on KD- tree for high-dimensional image descriptor matching,? J. Vis. Commun. Image Represent., vol. 44, pp. 106-115, 2017.

Jayaraman, U., Prakash, S. and Gupta, P. –An efficient technique for indexing multimodal biometric databases Umarani Jayaraman *, Surya Prakash and Phalguni Gupta,? Int. J. Biometrics, vol. 1, no. 4, pp. 418-441, 2009.

Li, L., Losser, T., Yorke, C. and Piltner, R. –Fast inverse distance weighting-based spatiotemporal interpolation: A web-based application of interpolating daily fine particulate matter PM<inf>2:5 </inf>in the contiguous U.S. using parallel programming and k-d tree,? Int. J. Environ. Res. Public Health, vol. 11, no. 9, pp. 9101-9141, 2014.

Mateos-García, D., García-Gutiérrez, J., and Riquelme-Santos, J. C. –On the Evolutionary Weighting of Neighbours and Features in the k-Nearest Neighbour Rule,? Neurocomputing, 2017.

Otair, M. –A Proximate K-Nearest Neighbour Based Spatial Clustering Using Kd-Tree,? Int. J. Data- base Manag. Syst., vol. 5, no. 1, pp. 97-108, 2013.

Rao, M. K., Swamy, K. V. and Sheela, K. A. –Face recognition using DWT and eigenvectors, 2012 1st Int. Conf. Emerg. Technol. Trends Electron. Commun. Netw., pp. 1-4, Dec. 2012.

Samet, Hanan. The Design and Analysis of Spatial Data Structures. Addison - Wesley Publishing Company, Inc., 1990.

Turk, M. and Pentland, A. –Eigenfaces for recognition,? J. Cogn. Neurosci., vol. 3, no. 1, pp. 71-86, Jan. 1991

Turk, M. and Pentland, A. –Eigenfaces for recognition,? J. Cogn. Neurosci., vol. 3, no. 1, pp. 71-86, Jan. 1991.

Turk, M. and Pentland, A. –Face recognition using eigenfaces,Proceedings. 1991 IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., pp. 586-591, 1991.
Muzammul, M. (2019). Education System re-engineering with AI (artificial intelligence) for Quality Im-provements with proposed model. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 8(2), 51–60. https://doi.org/10.14201/ADCAIJ2019825160

Downloads

Download data is not yet available.

Author Biography

Muhammad Muzammul

,
govt.college university faisalabad(gcuf),Pakistan
Muhammad Muzammul received his BSIT (2011-2013) from Govt. College University, Faisalabad (GCUF)-Pak. He worked as Lecturer 1.5 year in department of Software engineering GCUF. He worked as websoft trainer in Pro websoft org. He joined Fatima Jinnah college, Pak as lecturer and due to excellent performance he become Head of college in 2017. He started his MS (Software engineering) session 2017-2019 (GCUF), and he is top most student of class with CR ship and excellent in research with area of Automatic Machines learning to artificial intelligence with latest technologies trends and reengineering.
+