Survey onidentification and classification of waste for efficient disposal and recycling

 
 
 
  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract


    Waste management is a pervasive problem in today’s world and is rising continuously with rise in urbanization. For ecologically sustainable development, waste management is a vital requirement in many countries. It is very essential to sort the waste at base level so that there can be proper disposal of waste at the dumping sites. Sorting of waste requires more manpower and consumes more time too. Waste can be sorted and managed in numerous types of techniques. Analysing and classifying the garbage using image processing can be a very productive way to process waste materials. These papers talk about the traditional methods in which waste disposals are taking place. These also talk about the drawbacks faced by the already existing systems and ways to overcome it.


  • Keywords


    Waste Classification, Data Mining,Convolution neural Networks,Support Vector Machine

  • References


      [1] C. Capel, “Waste sorting - a look at the separation and sorting techniques in todayseuropean market,” Waste Management World, 2008.

      [2] S. Belongie, J. Malik, and J. Puzicha. Shape matching and object recognition using shape contexts. TPAMI, 24(4):509–522, 2002. , IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 24, NO. 24, APRIL 2002

      [3] R. Dror, E. H. Adelson, and A. S. Willsky.Recognition of surface reflectance properties from a single image under unknown real-world illumination.InIEEE Workshop on identifyingobjects across variation in lighting, 2001.

      [4] C. Liu, L. Sharan, E. H. Adelson, and R. Rosenholtz, “Exploring features in a bayesian framework for material recognition,” in Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on. IEEE, 2010, pp. 239–246.

      [5] A.Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in Advances in Neural Information Processing Systems 25,F. Pereira, C. J. C. Burges, L. Bottou, and K. Q.Weinberger, Eds. Curran Associates, Inc., 2012, pp. 1097–1105.

      [6] [Online]. Available: http://papers.nips.cc/paper/4824-imagenetclassification-

      [7] with-deep-convolutional-neural-networks.pdf

      [8] Comparing Deep Learning And Support Vector Machines for Autonomous Waste Sorting by George E. Sakr, Maria Mokbel, Ahmad Darwich, Mia Nasr Khneisser, Ali Hadi – 2016 IEEE International Multidisciplinary Conference on Engineering Technology

      [9] J. Donovan, “Auto-trash sorts garbage automatically at the techcrunch disrupt hackathon.” [Online].Available: https://techcrunch.com/2016/09/13/auto-trash-sortsgarbage-automatically-at-the-techcrunch-disrupt-hackathon/

      [10] G. Mittal, K. B. Yagnik, M. Garg, and N. C. Krishnan, “Spotgarbage: Smartphone app to detect garbage using deep learning,” in Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, ser. UbiComp ’16. New York,NY, USA: ACM, 2016, pp. 940–945. [Online]. Available: http://doi.acm.org/10.1145/2971648.2971731

      [11] Mindy Yang , Gary Thung “Classification of Trash for Recyclability Status”Stanford university Available: http://cs229.stanford.edu/proj2016/poster/ThungYang-ClassificationOfTrashForRecyclabilityStatus-poster.pdf

      [12] M A Hannan; Maher Arebey; R. A. Begum; H. BasriGray Level Aura Matrix: An image processing approach for waste bin level detection,IEEE 2011

      [13] T. Padmapriya, V.Saminadan, “Performance Improvement in long term Evolution-advanced network using multiple imput multiple output technique”, Journal of Advanced Research in Dynamical and Control Systems, Vol. 9, Sp-6, pp: 990-1010, 2017.

      S.V.Manikanthan and K.Baskaran “Low Cost VLSI Design Implementation of Sorting Network for ACSFD in Wireless Sensor Network”, CiiT International Journal of Programmable Device Circuits and Systems,Print: ISSN 0974 – 973X & Online: ISSN 0974 – 9624, Issue : November 2011, PDCS112011008.

 

View

Download

Article ID: 10513
 
DOI: 10.14419/ijet.v7i2.8.10513




Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.