Abstract
People who reside in remote rural communities face a plethora of challenges on a day-today basis. While benevolent donations in the form of equipment installations have been given to rural communities as a means to alleviate the challenges the communities face, little to no maintenance follow-up visits are conducted. The result is often that the donated equipment falls into a state of disrepair, leaving the community members frustrated with their initial challenges. The advancement of the internet of things in telecommunications and their relatively low-cost sensors, along with algorithms used in machine learning and artificial intelligence, has made it possible to implement predictive maintenance and cost-effective remote monitoring stations of rural infrastructure and equipment. Implementing cost-effective remote monitoring stations on rural equipment and infrastructure through the use of telecommunication technologies in conjunction with machine learning or artificial intelligence algorithm(s) will provide maintenance teams with more insight into the current operating condition of the rural infrastructure and equipment, which will, in turn, allow for more effectively planned maintenance trips to take place. This paper describes the use of the internet of things sensors and how they can be used in conjunction with the internet of things cloud and business process management notation to monitor the equipment better remotely and implement predictive maintenance for remote and rural communities.