A Novel Approach to Edge-Fog-Cloud Based Smart Agriculture

• Published in: 2023 International Conference on New Frontiers in Communication, Automation, Management and Security (ICCAMS) Vol. 1; pp. 1 - 5
• Main Authors: Shyam, Gopal Krishna, Chandrakar, Ila
• Format: Conference Proceeding
• Language: English
• Published: IEEE 27.10.2023
• Subjects: Cloud computing; Computer architecture; Energy consumption; Fog Computing; Internet of Things; Production; Smart agriculture; Telecommunication traffic
• DOI: 10.1109/ICCAMS60113.2023.10526104

Smart agriculture is a new concept that uses the latest technologies in the field of agriculture to improve quality and production. The development of the Internet of Things (IoT) has also brought a new dimension to the field of smart agriculture. The various technologies that are currently being used in the development of smart agriculture systems, such as the IoT, artificial intelligence, and cloud computing, are expected to greatly improve the efficiency and quality of the system. These innovations can help the agricultural industry reduce costs and improve production. However, it is seen that cloud systems are suited for huge data sets and its subset namely fog and edge could be used in the case of the smaller dataset. Further, due to the high cost of energy consumption, the implementation of the cloud layer creates a huge strain on the communication and information infrastructure of the system. In such cases, the fog and edge computing paradigm serve the purpose. Several studies have been conducted on the development of Edge-Fog-Cloud computing architecture, but none of them focused on the design of a system that can reduce its energy consumption. In this paper, we introduce a novel approach to the design and implementation of an Edge-Fog-Cloud-based smart agriculture system that can reduce energy consumption and thereby the network traffic. The proposed approach can be used to run applications based on its resource requirements and the data which are collected with the help of the sensors in the agricultural field using the appropriate technology. In addition to reducing the system's energy consumption, this method can also help optimize the network traffic.