In Africa, tea processing involves human sensory analysis to determine optimum production levels for desired quality yet, there are limits to humans’ precision and significant variability exists from person to person.
This process remains subject to errors of omission due to individualistic differentiations and reduces revenues to processors.
Through our research and data analytics, we have designed a mechanism using the Industrial Internet of Things (IIoT) data analytics approaches to increase processing efficiency to stabilize tea quality.
Our data analytics improve agro-processing design, and energy usage, and can be expanded to improve reliability in various dynamic African agro-industries from tea to coffee, and cocoa.