The Effects of Prepaid Metering Systems on Customer Satisfaction in Niger State, Nigeria

Energy consumers in Nigeria have long complained about Distribution Companies' unfair billing practices, exorbitant monthly electricity bills resulting from meter estimation rather than accurate meter reading and calculation based on uninterrupted electricity use. The objectives of the study were to establish the relationship between the prepaid metering system and customer satisfaction; and to evaluate the level of satisfaction with respect to the usage of the prepaid metering system in Niger State, Nigeria. In carrying out the study, the structured questionnaire was administered to 393 randomly chosen respondents drawn from prepaid meter users, out of which 344 responded generating a response rate of 87.5%. The data derived were subjected to spearman correlation and multiple regression models. The major findings from the study showed a significant, moderate and positive relationship between the prepaid metering system and customer satisfaction. Additionally, three significant predictors, Affordability, Availability and Flexibility with p < .01 are statistically significant. Further findings from descriptive statistics revealed that users had the highest level of satisfaction with the privacy they had as a result of no meter readers and no accumulated. The study concluded that there exist a positive and beneficial link between the prepaid metering system and customer satisfaction. The study therefore recommends the provision of a smart metering system, good customer care units and a marketing campaign for better knowledge of the prepaid metering system.

The Design and Performance Evaluation of a Wireless Sensor Network Based Irrigation System on Different Soil Types

In the Nigerian economy, agriculture plays a very important role, and most of its people depend on it for their livelihood. Agricultural practices in the country are still mainly based on conventional, traditional methods of farming which usually results in wastage of water resources and low production of crops to meet the country's demand. There is a need to transform farming from the traditional way to a more efficient method with optimum water utilization. Irrigation is an assistive measure to salvage the problem of inadequate water for dry season farming. Irrigation consumes a lot of water, time and must be done on a timely basis. The automated irrigation system helps to curb the problem of overwatering and under watering of the land. This research proposed an Arduino-based smart irrigation system using a wireless sensor network to overcome the problem of overwatering, underwatering, and efficient time utilization in farming. The system is implemented using Arduino IDE, Proteus Simulation Tools, and Blynk Platform. The effect of the four-mobile network: MTN, GLO, Airtel and 9mobile on response time for Gidan- Kwano area was evaluated. Testing carried out on the system resulted in a response time of 0.75 seconds for Glo 2G network and 0.45 seconds for Glo 4G network. Less than 1sec in the worst-case scenario. This makes the system effective in terms of time response, thereby eradicate the waste of time that manual system operation poised to irrigation scheduling. Also, the appropriate soil moisture content is maintained, whether it rains or not. This reduces excesses and ensures healthy plant growth, increasing agricultural productivity, and cultivating crops are made possible throughout the year. The system also will help in driving agricultural innovation through the use of IoT.

Assessing Theoretical Frameworks, Human Resources Management Implications and Emerging Technologies on the Water, Energy and Food (WEF) Nexus

The interactions of water, energy, and food resources resulting in WEF nexus thinking have been conceptualized as an integrated framework to achieve the security of the three vital resources. However, there are some gaps in WEF nexus research, which constrains the understanding and actualization of the nexus. Hence, this review paper aims to assess theories, human resource management implications, and emerging technologies' effect in understanding the nexus for its actualization. The research employed a qualitative research methodology to achieve the research objectives. The research findings revealed six (6) significant theories that can aid the understanding and actualization of the WEF nexus. The research also revealed that human resource management is strategic, highlighting the need for nexus thinking among human resources. Furthermore, the study revealed the three major emerging technologies of Artificial Intelligence, Big data analytics, and Internet of Things (IoT), which are shaping the WEF nexus through innovations and shaping the nature of the nexus. The study concluded that there is an interaction between the theories and human resources management for attaining the WEF nexus, which affects the extent of the sustainability of the innovations introduced by the emerging technologies. The study recommended quantification of the theories, training on nexus thinking of the current human resource in the WEF sectors, and capital investment on emerging technologies in the WEF nexus.

Modelling the Impacts of Climate Change on the Yield of Crops

This study aims to improve the understanding of the impact changes being experienced in our climate system will have on the level of crop productivity in the immediate period as well as in the nearest future. Nigeria was used as a case study and an observed climatic dataset was obtained and used alongside collected 20 year cassava, rice and soybean yield data to develop models that were applied to estimate future crop yield. Four statistically downscaled and bias-corrected Global Climate Models (GCMs): NOAA, MIROC5, ICHEC, and NCC performed simulations for the period 1985–2100 under the Representative Concentration Pathway RCP8.5. These were used to predict how the yields of cassava, rice and soybean will be in the years 2020-2050 and 2070-2100 for the 36 states in Nigeria and the FCT. 89 Empirical models were developed to estimate the yields of the three crops earlier mentioned across Nigeria with their coefficient of determination (R2) ranging between 15% - 99%. The result showed an increase of 3.91% (P<0.001), 0.08, 1.79 (P<0.1) and a decrease of 0.93% for cassava yield for ICHEC, MIROC, NOAA and NCC respectively. It also projected an increase in yield of 8.88% (P<0.001), 7.77% (P<0.001), 6.62% (P<0.001) and 8.85% (P<0.001) for Rice yield using climatic data from ICHEC, MIROC, NOAA and NCC respectively. Soybean, increase in yield are 2.81% (P<0.01), 5.84% (P<0.001), 11.38 (P<0.001) and 9.06% (P<0.001) for ICHEC, MIROC, NOAA and NCC respectively.

The Awareness and Adoption of Artificial Intelligence for Effective Facilities Management in the Energy Sector

Digitalization and artificial intelligence (AI) have infiltrated most sectors of the economy, including the energy sector, where they have been extensively investigated. The aim of the study is primarily to assess the awareness of AI in facility management, and to identify the prospects and challenges of the adoption of AI in the energy sector. The study adopted the quantitative methodology approach, using a structured questionnaire to a sample size of 384 respondents. The questionnaire was administered to professionals such as mechanical, civil, electrical, computer, and mechatronics engineers, and project managers within the North-central geopolitical zone of Nigeria. Data gathered was analysed using descriptive analysis (mean value, weighted total, and relative importance index). The study based on findings concludes that there exists high awareness level about the concept of AI in the energy sector. However, regarding the awareness about some selected AI technologies, machine & deep learning, robotics, and speech recognition had high awareness level. The study also concludes that improved energy management, efficiency and transparency, remote reading of energy meters, and improved planning, operation & control of power systems were prevalent prospects of AI adoption. The major challenging factors to the adoption of AI in the Nigerian energy sector are outdated power system infrastructure, cellular technologies, lack of qualified experts and data science skills, and growing threat from cyber-attacks. The study recommends improved awareness and technical know-how of energy sector personnel, and provision of adequate power system infrastructure to provide stable power supply.

Farmers-Herders Conflict and Nigeria’s Quest for Food Security: The Imperative Need for Information Communications Technology

Although, Nigeria is chiefly known for its oil and gas production, agriculture employs about 70 per cent of its labour force. Nigeria has experienced severe farmers-herders conflict that has negatively influenced her agricultural production capacity, resulting in severe food insecurity. Tensions have grown over the past decades, with increasingly violent flare-ups between the farmers and the herdsmen spreading across the entire country. In recent times, many scholarly studies and inquiries on the impact of Information Communications Technology, particularly with respect to promoting food security in Nigeria, have been engendered mainly by the need to ensure greater agricultural outputs among farmers and other agriculturists. However, only scanty attention had been devoted to the need to understand the imperativeness of the use of Information Communications Technology in the quest to proffer solutions to the incessant farmers-herdsmen conflicts that have also contributed to the unpalatable state of food security in Nigeria. The study adopts Karl Marx’s Conflict Theory as a framework of analysis and qualitative date elicited through content analysis of desktop date. Hinging on this theory, this study contends that the farmers-herdsmen conflict is inevitable like every other conflict due to the competition for limited land resources. The study however found out that why the farmers-herdsmen conflict has persisted, among many other factors, was due to the failure of relevant stakeholders to leverage on the possibilities of Information Communications Technology to address the technological gap in the conflict. While further findings suggest that the principal causes and aggravating factors behind the escalating conflict are climatic changes; population growth; technological and economic changes; crime; political and ethnic strife; and cultural changes, the lack of use of Information Communications Technology in the areas of educating both the farmers and herders, awareness creation, crime reporting and conflicts resolution further compounds the farmers-herdsmen conflicts. This study recommends the need for proper and improved use of I.C.T. in the processes to address the farmers-herdsmen conflicts.

Assessment of the Availability and Penetration of Solar PV, Wind and Biogas in Ghana

Access to energy is pivotal to the socio-economic growth of many developing countries, including Ghana. Energy generation from fossil fuels is not sustainable and leads to global warming, which is detrimental to the environment. This study seeks to establish how renewable energies are embedded and utilised in the Ghanaian energy system and the factors that can expedite the speedy penetration of renewable technologies into the country, particularly solar PV, wind, and biogas. The study adopted a mixed research approach which includes quantitative and qualitative studies. The findings revealed that solar energy is the most available resource in the country compared to other renewables. It was also indicative that integrating solar PV, wind and biogas in the national electricity grid will improve the percentage of energy generation mix, which will help sustain constant power supply, reduce the cost of energy charges, and consequently improve the country’s economy. The results also showed the possible factors that affect future penetration of these technologies, including unavailability of consumer financing opportunities, inadequate training facilities, lack of adequate regulations/policies, lack of information on the cost and benefits of renewable energies. The six findings of the paper established the availability of renewables in Ghana and the prospect of their related technology. While solar PV is on the ascendency, biogas is progressing gradually and wind is moving at a snail’s pace. This study significantly established the benefits of incorporating solar PV, wind and biogas in the Ghanaian energy mix to improve the electricity supply and further outlined the impeding factors that need to be improved upon through policy.

An Intelligent System for Load Forecasting on a Distribution Network

This paper presents an Adaptive Neuro-Fuzzy Inference system (ANFIS) technique for medium-term load forecasting in a distribution network. This technique is an integrated system consisting of fuzzy logic systems and Artificial Neural network (ANN). The inputs to the system include days of the week, temperature, time, current and previous hourly load on the distribution network. The data collection is within the period of two years. The formulation and mapping of the input data is done using fuzzy logic system and ANN are employed for generation of inference. The experimental results show the average load pre-diction accuracy of 87.23% and regression coefficient of 0.873. The analysis of the proposed ANFIS for load forecast is effective in planning, managing and organizing the electric load forecast with accurate prediction.

Fuzzy Axiomatic Approach to Blue-green Infrastructure Strategy Selection: A Sustainability Perspective

Flood management is a global problem that has created immense contributions from researchers and practitioners, especially those in developing countries. These people often seek ways to minimise the aftermath of a flood. Recently, they are making a case for sustainable solutions to flood management. This study, therefore, contributes a sustainability model that addresses the problem of blue-green technology selection to the current discussion on flood management. It coupled the techno-economic, social, and environmental impact of a blue-green technology using the unique attributions of three multi-criteria decision-making tools: best-worst method, fuzzy axiomatic method and VIKOR; its performance was investigated with qualitative data sets that were obtained from experts. The outcomes of the investigation showed that techno-economic criteria contributed about 88.18% to the ranking of blue-green technology. The most and least suitable blue-green technologies for a community in Nigeria are Rainwater and floodwater harvesting and Retention lake, respectively. With these results, the proposed model will aid decision-makers strategic and tactical criteria that can be used to evaluate blue-green technology selection.

Design and Implementation of a Quadcopter Based on a Linear Quadratic Regulator (LQR)

This paper presents the design and construction and control of a quadcopter drone for Aerial Data Collection (ADC). The frame of the drone was designed using CadDian Software and the parts were printed using a 3D printer. The flight controller was based on Arduino board using an Atmega328p microprocessor with GSM, GPS and GPRS for sending data over the internet and also enhancing long range flight. A feedback control system was developed and tested to control the stability of drone. The proposed control strategy of the drone was tested for a case of pursuit of trajectory and also for speed of response and the findings were very positive confirming the appropriateness of the control measures for independent and autonomous flying with promising precision. This Unmanned Aerial Vehicle (UAV) fitted with IoT has the capability of collecting and sending data over the internet and therefore can be used in many applications including risk assessment, forestry management, urban planning, coastal zone management, infrastructure monitoring, post-disaster damage assessment and delivery of medical supplies.