Development of software as a service (SaaS) on Amazon cloud for rice crop monitoring | |
| Author | Das, Pratyush Kumar |
| Call Number | AIT Thesis no.RS-18-11 |
| Subject(s) | Drone aircraft Software engineering Cloud computing Aeronautics in agriculture Amazon Web Services (Firm) |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Remote Sensing and Geographic Information System, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Abstract | Agriculture sectors remain one of the most important sectors for developing countries for alleviating poverty and achieving growth. Thailand remains one of the major exporters of rice in the world. In recent year with rapid development in IT sectors have been a boon for the agricultural sector. The use of drones, sensors and precision agricultural tools have given rise to smart farming. Out of all these technologies recently the use of drones has been immensely popular. But the problem remains is in terms of cost associated with the processing of data which requires high computing resource in terms of hardware and also professional software. The use of this software also requires skilled manpower. Even after processing the data proper 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 services of Amazon i.e. Amazon Web Services. This developed system has been based on Software as a Service (SaaS) concept as a result of which user can access the system with a standard browser and internet connectivity. This developed system provides user to upload farms in GML format and images collected from UAV mounted sensor in JPEG format. Vegetation Index i.e. NDVI module has been added to the system which calculates the average NDVI for farms and stores them a biweekly basis in the database. This developed system stores average NDVI for each farm for two season. One is for present and the other is for the previous season. The previous season NDVI value is used by the system for comparing with the present season. This comparison done by the system is made into graphs and sent to farmers with a message about the condition of the farm using LINE Notify services. Finally a cost analysis was done for the developed system as compared to setting up a workstation of same computing resource as cloud instance. It was found that the cost of processing on the cloud can reduce cost by 123% as compared to setting up a workstation. |
| Year | 2018 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Remote Sensing (RS) |
| Chairperson(s) | Sarawut Ninsawat |
| Examination Committee(s) | Tripathi, Nitin Kumar ;Soni, Peeyush ;Surat Lertlum |
| Scholarship Donor(s) | AIT Fellowship |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2018 |