Electricity usage monitoring systems play a vital role towards raising energy utilization awareness for consumers. Existing solar mini-grid infrastructure, however, lacks a user-friendly two-way platform to allow consumers to access information about electricity consumption. This paper proposes a cloud-based, two-way energy usage monitoring system that will allow both utility companies and consumers to access energy consumption data in a user-friendly way through a web platform. The system requirements were collected via questionnaires, interviews, and observations conducted at two solar mini-grids centres located at Arusha and Kilimanjaro regions in Tanzania. The system uses a Low Power Area Network (LPWAN) and the existing GPRS network to monitor electricity consumption data between smart meter units and the cloud server. Also, a virtual bill payment module and usage status feedback functionality have been integrated into the system to increase awareness of the cost-effective use of electricity and hence, achieve the sustainability of solar mini-grids. By using both white-box and black-box system testing approaches, findings show that the system will not only raise awareness among customers about the economical usage of electricity, but it can also be used by mini-grid companies as a source of data to determine current and future energy demands to minimize large investment costs.

Wireless sensor networks (WSN), when applied to the field of water quality monitoring and management, has the potential to bring numerous benefits as compared to traditional methods since it is accurate, reliable in remote areas and in the tough condition such as during rainy seasons, and less costly. With the ever-growing application of Internet of Things (IoT) and technology in general, sensor devices have become less expensive and widely used in many applications that require remote monitoring. In this work, we present an innovative and secure water monitoring and management system using remote sensor prototype, which has been developed to monitor physiochemical parameters including pH, Turbidity, Temperature, and Dissolved Oxygen. Qualitative research methods were used for gathering system requirements through questionnaires and interviews conducted in Pangani water basin authority, in the United Republic of Tanzania. Documents were also reviewed to provide secondary knowledge. Furthermore, the system was developed using Dynamic System Development Methodology (DSDM). Firstly, the proposed system prototype is able to provide real-time measurements accurately. Secondly, the proposed system uses Advanced Encryption Standards to provide a secure transmission and storage of data transmitted from remote sensor nodes to a central database system. Thirdly, the web application was developed for data visualization using tabular and graphical formats. Lastly, the system prototype provides decisions support on quality of water present in Pangani river basin by evaluating sensor measurements and sends SMS alerts once the measured value is above the recommended standard values.

For more than half a century, Forward Error Correction Convolutional Codes (FEC-CC) have been in use to provide reliable data communication over various communication networks. The recent high increase of mobile communication services that require both bandwidth intensive and interactive Real Time Applications (RTAs) impose an increased demand for fast and reliable wireless communication networks. Transmission burst errors; data decoding complexity and jitter are identified as key factors influencing the quality of service of RTAs implementation over wireless transmission media. This paper reviews FEC-CC as one of the most commonly used algorithm in Forward Error Correction for the purpose of improving its operational performance. Under this category, we have analyzed various previous works for their strengths and weaknesses in decoding FEC-CC. A comparison of various decoding algorithms is made based on their decoding computational complexity.