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Mr. Saud Mohammad Mostafa, Full-Time COE MS Student, will defend his MS Thesis on Wednesday, November 25, 2020, at 01:00 p.m. Online (By Using Microsoft Teams). His MS thesis title is "IIoT Based Framework for Large-Scale Distributed Smart Farms". His thesis advisor is "Dr. Basem Al-Madani, Assistant Professor, COE Department". You are cordially invited to attend by clicking the following link ""
The population would reach ten billion by 2050, and experts believe that the agricultural sector needs to boost production by 70% to satisfy the demand. Traditional farming practices rely on primitive technology that creates a yield gap with low productivity. A paradigm shift towards merging new technologies in the agriculture sector would enhance productivity, optimize cost, and encourage sustainable development. In this research, we review the necessity for the fusion of the Fourth Industrial Revolution technological approach in the agricultural domain. We discuss the gap in supply chain management for the Industrial sector and Agricultural sector and identify the issues of vendor-specific production systems. We propose an Industrial Internet of Things (IIoT) based framework with a multimodal communication model for the systematic integration of multi-vendor agricultural production systems. Our model utilizes the Data Distribution Service (DDS) middleware to enable communication between heterogeneous production systems to perform farming operations in a coordinated manner. The communication model complies with the automation levels in the industrial sector, and the use of Quality of Service (QoS) policies adapts the system according to domain requirements. Case study based analysis and experimental work are conducted to evaluate the performance of the system in terms of throughput, average latency, and packet delivery ratio. The results suggest our model can enable interoperability between multi-vendor production systems in real-time while incurring minimum latency. The system improves performance with the use of batching during communication.

Expiry: 01 Jan 2021