Precision Agriculture which includes the implementation of smart farms is gradually becoming commonplace in our present world. The Internet of Things (IoT) and also Analytics techniques are useful tools for the actualization of smart farms as they allow for information dissemination to rural farmers and also serve as a platform for monitoring farm activities. When farm activities are properly monitored, food production is optimized. As the world’s population grows, there is a greater challenge of the availability of food. The combination of IoT and data analytics has not been fully explored for Smart farming especially in developing economies. This paper proposes a FarmSmart Application using an IoT-based mobile monitoring system that combines sensors, and data analytics to manage irrigation processes and broadcast Agricultural information to farmers. The FarmSmartApp was implemented on the IntelliJ IDE using C++ and MongoDB.Python and Excel were used for the data analytics. The effectiveness of the proposed system is examined on a real-world dataset harvested from the mounted sensors. Also an initial evaluation of the system is done by stakeholders. Simple Analysis of Variance of light, moisture and temperature led to the rejection of the null hypothesis of no significance difference in mean effect among the variables since fcalc is greater than fcrit justified by p value less than 0.05. On the system evaluation, 97 % of the examined stakeholders agreed that the system delivered on the agreed functionality .The system therefore has the capacity to provide farmers with useful Agricultural information to guide irrigation procedures and Agricultural decision making

This research study aims at developing a collaborative research tool using distributed servers to enhance collaborative research among Universities and Industries to promote innovation. The Adaptive Software Development model was employed due to the innovative nature of the study. Requirements were gathered from key stakeholders to determine the system architecture and various models that supported the system development process. The testing procedure demonstrated that three (3) separately located servers representing University A, University B and Industry Players worked together as one unit such that all users could form Research Teams and collaboratively conduct research work on the platform to boost University-Industry partnership for innovation.

This research study aimed at developing a distributed system of web-based collaboration that would create a research and innovation ecosystem for university-industry partnership. Based on in-depth literature review, the focus-group approach to qualitative research was conducted with key stakeholders in university-industry partnership coming together to understand the research problem and system requirements. The requirements gathered at the project initiation stage guided the system design and implementation of a distributed collaborative research and innovation system that runs on three separately located servers: two for two different universities and one for all industry players. The system developed was modeled to describe how it works and to demonstrate how it would meet the identified functional requirements. Recommendations were given to guide further research and development that would improve the impact of this research study.

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