Sheeza Ahmad1*, Muhammad Wassay2* and Muhammad Ans Hussain3
1Department of Computer Science, Faculty of Computing, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan 2MOA Key Laboratory of Crop Ecophysiology and Farming System in the Middle Reaches of the Yangtze River, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China 3National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
Sheezaahmad26@outlook.com, muhammadwassay@webmail.hzau.edu.cn
Agricultural research is revolutionized by cloud computing offering scalable and cost effective means of supporting the management of complex datasets such as the genomic, environmental and sensor data. However, the challenges associated with semi structured volume and complexity of multiple varieties of data make it difficult to manage through traditional data management and hence need advanced computing frameworks for efficient data storage, integration, and analysis. Real time data processing and decision making is the key point in the precision agriculture and smart farming systems and cloud computing enables this. It provides global research collaboration to facilitate multi user access to big data analytics, and makes efficient AI driven use of agricultural innovations. This paper discusses in detail the core functions of the cloud computing solutions include Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS), how they increase the speed and scope of the genomic research, high throughput phenotyping, disease detection, and precision farming. Automated crop monitoring, predictive modeling and early-warning systems of pest and disease can be conferred by integration of IoT devices, AI and machine learning with the cloud platform. However, despite these advantages, data security, privacy issues, rural communication connectivity, and lack of integration between sources of other data continue to be major impediments to the uptake of this technology. The optimized application of various technological trends such as AI, edge computing, and blockchain will be the future of cloud computing in agriculture sector to ensure data security as well as better transparency and decision making in localized conditions. In particular, cybersecurity risks will need to be addressed, digital accessibility will need to be improved, and energy efficient cloud solution will need to be developed for ensuring the long term sustainability and effectiveness of cloud driven agricultural research and innovation.