Development of Software as a Service (SaaS) on Amazon Cloud for Rice Crop Monitoring

Name: Pratyush Kumar Das

ID: –

Title: Development of Software as a Service (SaaS) on Amazon Cloud for Rice Crop Monitoring

Type: Thesis

Abstract

Agriculture sectors remain one of the mostimportant sectors for developing countries for alleviating poverty andachieving growth. Thailand remains one of the major exporters of rice in theworld. In recent year with rapid development in IT sectors have been a boon forthe agricultural sector. The use of drones, sensors and precision agricultural tools have given rise to smart farming. Out of all these technologies recentlythe use of drones has been immensely popular. But the problem remains is interms of cost associated with the processing of data which requires highcomputing resource in terms of hardware and also professional software. The useof this software also requires skilled manpower. Even after processing the dataproper information is not provided to the farmers. All these challenges make farmers skeptical about using technology in agriculture.

This study aimed at developing a system for the agricultural sector and providing it as service to farmers using cloud servicesof Amazon i.e. Amazon Web Services. This developed system has been based onSoftware as a Service (SaaS) concept as a result of which user can access thesystem with a standard browser and internet connectivity. This developed systemprovides user to upload farms in GML format and images collected from UAVmounted sensor in JPEG format. Vegetation Index i.e. NDVI module has been addedto the system which calculates the average NDVI for farms and stores them abiweekly basis in the database. This developed system stores average NDVI foreach farm for two season. One is for present and the other is for the previousseason. The previous season NDVI value is used by the system for comparing withthe present season. This comparison done by the system is made into graphs andsent to farmers with a message about the condition of the farm using LINENotify services. Finally a cost analysis was done for the developed system ascompared to setting up a workstation of same computing resource as cloudinstance. It was found that the cost of processing on the cloud can reduce costby 123% as compared to setting up a workstation.

Keywords: Software as a Service (SaaS), Amazon Web Services (AWS), Unmanned Ariel Vehicle (UAV), Normalized Difference Vegetation Index (NDVI), LINE Notify Services.

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