Community Cloud Model for Infrastructure –As-A-Service in Learning through Content Sharing - Ochango, Vincent Mbandu; Mwangi, Waweru; Okeyo, George (International Journal of Computer Sciences and Engineering, 2019)
Cloud computing is growing rapidly, with its server farms evolving at a remarkable rate. This paper tries to elaborate on a community cloud model that tries to use web application to identify maize disease through image matching. The model tries to match uploaded images with the images stored in the file system and if a match is found, the matching image is displayed together with its associated disease. The images were matched based on time, location and images collected from secondary sources to see if the disease can still be identified. All the images matched were successful and the appropriate diseases associated with the images were identified. The load balancing technology was also incorporated into the model mainly for the accessibility of the web application and to avoid overloading of one server. The image matching results were collected and tabulated as shown in chapter four and the results clearly indicated that the community cloud model really helped users to identify possible disease through the web application hosted on the community cloud model servers.