Prediction of Banana Quality Using Sensor Network
Efficient classification of fruits and vegetables is one of the major challenges of the fruit industry. In the case of large-scale production of fruits and vegetables, storage and maintenance are the main challenges. Some of the techniques developed to do this based on image processing and hyperspectral imaging. Available techniques can classify fruits and vegetables based on their external appearance. It minimises the probability of getting correct prediction results. There is need of automated framework, which should consider not only external factors but also internal properties of fruit sample. This work aims to develop and analyze framework to predict fruit quality using sensors and machine learning. To achieve this, non-destructive experimental setup is designed to extract fruit samples gaseous sensory attributes. Banana fruit samples considered to carry out this experiment. Extracted attributes from fruit samples are stored and clustered into three classes. These three clusters named as, Eatable, Not Eatable and May be Eatable. After clustering, fuzzy inference system is developed based on fuzzy rule-based construction. The designed framework could predict banana samples quality, approximately 88% correctly.
Disclaimer/Regarding indexing issue:
We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information. Also: DOI is paid service which provided by a third party. We never mentioned that we go for this for our any journal. However, journal have no objection if author go directly for this paid DOI service.