MST-School of Engineering and Technology

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This collections contains bibliographic information and abstracts of Master theses and dissertation in the School of Engineering and Technology held in Kenyatta University Library

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    A Hybrid Model for Detecting Insurance Fraud Using K Means and Support Vector Machine Algorithms
    (Kenyatta University, 2024-10) Muthura, Brian Ndirangu
    Medical insurance fraud is a significant issue in the healthcare sector, commonly characterized by fraud patterns such as misrepresentation of services, false claims, and identity theft. These patterns contribute to severe data class imbalances, with legitimate claims vastly outnumbering fraudulent ones, complicating effective detection. Current fraud detection methods struggle to address these evolving patterns and manage imbalanced datasets. This study employs a mixed-methods approach, integrating an extensive literature review with quantitative analysis of historical medical claims data. The research develops and evaluates four machine learning models: a standalone Support Vector Machine (SVM), a tuned SVM, a hybrid model combining K-Means clustering with SVM, and a tuned hybrid model. The models were compared using key metrics, including accuracy, precision, recall, and F1 score. Results show that the tuned hybrid model achieved the highest performance with an accuracy of 97.49%, demonstrating its superior ability to detect fraudulent claims compared to the standalone and default hybrid models. Future work will focus on further improving the computational efficiency of the hybrid model and exploring its adaptability to new and evolving fraud patterns in real-time environments. This research significantly advances fraud detection by offering a robust solution that tackles class imbalances and adapts to evolving fraud schemes
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    A Multi-Agent Monitoring System for Computer Networks
    (Kenyatta University, 2025-09) Amwayi, Harrison Makokha
    In today’s business environment, reliable network infrastructure is critical for day-to-day operations. As networks grow in complexity, efficient monitoring systems are essential to ensure the performance and availability of network devices. This study investigates the use of multi-agents in monitoring computer network devices, focusing on the application of autonomous agents in gathering and analyzing network data using the Simple Network Management Protocol (SNMP). It explores existing multi-agent frameworks and their limitations, followed by the design and implementation of a new model that integrates SNMP agents and Apache Kafka for scalable data ingestion and processing. The developed solution is designed to address concerns of scalability and network congestion, typically associated with centralized monitoring systems. By leveraging on Apache Kafka as a distributed messaging system, polling tasks are dynamically assigned across multiple agents, ensuring load balancing and fault tolerance. Additionally, feature selection is employed to reduce latency and minimize network congestion. The system was tested to evaluate its performance in real-time monitoring scenarios, demonstrating improvements in scalability and efficiency. This research concludes that multi-agent systems, combined with Apache Kafka, provide a robust model for real-time monitoring of network devices, offering enhanced scalability and reduced latency compared to traditional centralized approaches. Future work may involve refining fault-tolerance mechanisms and exploring additional autonomous agent models for other network management tasks.
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    Adaptive Pedestrian Detection System Based on Deep Learning
    (Kenyatta University, 2025-03) Aquino Nyapara Joctum
    The existing pedestrian detection algorithms have the potential to improve road safety on a regional level, however their effectiveness in dynamic rural and urban environments remains unexploited. With this potential capability, their efficacy remains uncertain due to infrastructure and operational limitations. Nationally, integration into Kenya’s transport system is still in its infancy, with challenges in policy, infrastructure, and technological readiness limiting real-world deployment. The problem lies in the inability of current systems to provide accurate and timely detection, particularly in complex road topologies such as Type-S roads with sharp curves and frequent occlusions. To address this, this research proposes a YOLO-APD network to enhance detection accuracy and achieve real-time processing. A cost-effective RGB camera in the CARLA simulator was used to generate a custom dataset reflecting diverse traffic scenarios. Enhancements to the YOLOv8 baseline include a novel SimSPPF module for improved feature extraction and speed, a modified detection head with a gather-and-distribute mechanism, and C3Ghost modules for balancing efficiency and accuracy. The model was evaluated through ablation experiments, algorithm comparisons, and robustness tests. Results show YOLO-APD achieved a mean Average Precision (mAP) of 97.8%, with pedestrian detection exceeding 99.5%, outperforming state-of-the-art models. The model demonstrated robust performance with a 94% F1 score, validating its generalization ability in challenging environments. By enhancing detection accuracy and efficiency in Type-S roads, YOLO-APD presents a viable solution for improving autonomous navigation in complex traffic environments.
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    An Ensemble Feature Selection Model with Machine Learning Model for Detection of Fraudulent Motor Vehicle Insurance Claims
    (Kenyatta University, 2025-05) Wambu, Anthony Mwiti
    Insurance companies are continuously inventing new competitive insurance products in order to enlarge their market share. This has continuously created opportunities for insurance fraud as well. Despite the insurance industry having extensive motor vehicle policy data and claims information, fraudulent claims remain a significant challenge in motor vehicle insurance. Proper analysis of this data can result in development of more efficient methods for identifying fraudulent claims. The challenge lies on how to extract valuable insights and knowledge from this data. This is because insurance datasets inherently include noisy features or low-quality subsets of data. This study used feature selection techniques to select relevant features from motor vehicle insurance claim dataset. The selected features were then used in training machine learning model. The machine learning model consisted of multiple machine learning algorithms whose individual prediction results were combined by use of a voting method. This helped to improve classification performance. Machine learning model’s performance with feature selected dataset and with full dataset was then evaluated using recall, precision and F1- score. The results indicated that the model trained with feature selected dataset performed better than the model trained with full dataset attaining higher values in recall, precision and F1-score. This indicated improved capability in minimizing false negative and improved overall effectiveness in fraud detection. For feature work the model developed for detecting fraudulent motor vehicle insurance claims can be enhanced by integrating machine learning techniques with nature-inspired optimization algorithms. This will help in better handling of extensive datasets and result to development of more rapid and effective models for identifying false claims.
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    Application of mobile phone in crime prevention within Central division, Nairobi city County
    (Kenyatta University, 2017-08) Wambugu, Paul M.
    ABSTRACT The study sought to establish application of mobile phones applications by police officers in crime prevention in Central Police Division, Nairobi City County. Application of mobile phone in the police service is underutilized making the organization not to fully benefit from its usage. Understanding use of mobile phone applications by the police officers may assist the organization in crime prevention efforts. Due to its ability to engage consumers in a timely and direct manner at low costs, mobile phone applications are relevant for the police organization. The study was guided by the Mobile Technology Acceptance Model (M-TAM) as the success of the mobile phone implementation depends on perceived usefulness (PU) and perceived ease of use (PEOU).The targeted population in this study was police officers serving at Central Division of Nairobi County (782). A sample of 155 police officers was recruited using random stratified sampling procedure for this study. Questionnaires were used for data collection for both qualitative and quantitative data. Qualitative data was coded and analysed thematically after interpretation of theme while descriptive data was analysed using descriptive statistics by use of Statistical Package for Social Sciences (SPSS version 20.0). Mobile phone was found to be effective tool in prevention of crime in Nairobi Central. Mobile phone applications such as Facebook, Whatsapp, Twitter, emails and short text messages were found through adapted technology acceptance model (TAM) as to effectively contribute to crime prevention based on respondents’ perspective. Police effort to use mobile technology was found to have significant effects on crime prevention. Based on these findings, the study recommends development of customised police mobile phone applications and enhancement of applications use through capacity building among police officers.
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    Archives Management and Service Delivery: The Case of Kenya National Archives and Documentation Services
    (Kenyatta University, 2023-06) Isoka, Bathsheba Ratemo M.
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    Assessment of water resources utilization and management in chahi sub-catchment, Kisoro district, Uganda
    (2013-07-23) Tera, Marahi Moses
    There is a growing global concern over the future of the world‟s water resources due to the preceding vulnerability. Some of the factors contributing to the increase in water resources vulnerability include population growth and poor land use practices. This study assessed the local uses and management of water resources and the local coping mechanisms, identified the drivers of water resources scarcity and evaluated the opportunities and challenges of managing water resources in Chahi sub-catchment, Kisoro District, Uganda. To achieve the objectives of the study, the following empirical tools were used; a structured questionnaire, key informant interviews and field observation guides. A total of 100 households and 20 key informants were interviewed. Numerical tools for data analysis comprised descriptive statistics and non-parametric test. SWOT analysis tool was used to examine the challenges and opportunities. The study identified pipe borne water (89%), stream (58%), rain (40%) through roof catchment and vendors (8%) as the major sources of water in the sub-catchment, with domestic (100%) and agricultural (24%) being the major local uses of water. Women played a key role in the management of water sources, making use of the water and fetching of water from the water sources. Construction of water points, maintenance of available water points, fencing of the water source, participatory planning in water management, equitable distribution of water tanks and training on water management were identified by households as interventions to ensure sustainable water supply and management in the sub-catchment. Drivers of water resources scarcity in the sub-catchment included climate change (98%), poverty among the households (80%), population growth (77%), pollution (41%), inadequate information on water management (33%), land use practices (20%) and deforestation (16%). Various coping mechanisms; domestic rainwater harvesting (DRWH), water storage during plenty, water pricing, use of earthen pots, moving long distances and innovative agricultural practices were being used by the households. However, not any of all these coping mechanisms considered depicted a significant relationship with the households‟ longevity in the sub-catchment. Major challenges hindering water resources management (WRM) in the sub-catchment are; low coverage of rainwater harvesting technology at household level, lack of internal training on WRM technologies and inadequate support of water initiatives by the households. Conversely, the opportunities established include; location, support from the Central Government through the District Local Government and involvement of different stakeholders in water management. The study concludes that water shortage appears as a powerful incentive to change, eliciting major adaptations and coping strategies from users. This study recommends focus on building more water infrastructure and involvement of the households in the planning and allocation of water resources. This will contribute to improved understanding of the need for efficient water resources utilization and management on household livelihoods and also help design appropriate WRM strategies for the poor peasant farmers and provide guidance for policy makers for similar situations in Uganda and beyond.
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    Automated Examination Generation using Natural Language Processing and Artificial Neural Network
    (Kenyatta University, 2023) Ndirangu, Peter Ndegwa; Elizaphan Maina
    The examination process is a key activity in evaluating what the learner has gained from the study. Institutions of Higher Learning (IHL) perform the activity by administering tests which comprises of questions and answers. Cognitive level, weight of the question, and topic coverage are key factors to consider when setting exams. The world today has largely focused on the automation of exam generation which has been ongoing with dire need during the period of the Covid-19 pandemic when education was greatly affected, leading to embracing online learning and examination. The process has taken shape; however, the automation process can be improved by incorporating machine learning algorithms in the process of setting examination. In view of this, the project focused on implementation of a question classification model that uses Neural-Network algorithm (NN) and Natural Language Processing (NLP) to determine questions cognitive levels based on the revised Bloom's Taxonomy. The iterative method of software development was adopted to provide room for continuous improvement. The developed model was put under test with a couple of questions obtained online. The effectiveness of the model was determined by subjecting it into database of 600 questions resulting to an accuracy of about 71%. An Application Programming Interface (API) and Moodle Learning Management System (LMS) plugin were consequently developed to allow integration of the model with an existing system. The deep learning approach was applied to predict cognitive levels of questions based on Bloom’s taxonomy and the resulting questions were made available to the instructor through the LMS interface. Future research should focus on the use of convolutional reinforcement learning to establish its effectiveness in question classification as well as perform comparison with various algorithms.
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    Calcium Chloride Supported on Purified Spent Bleaching Earth as Potential Adsorptive Material for Air Dehumidification Application
    (2013-03-22) Mathaga, Kihara John
    Thecosmic limitation of high humid environment in tropic regions spurs a lot of interest to the developmentof low cost desiccants. Calcium chloride has been indicated as the oldest adsorbent desiccant among chemicals and gas dehydration industries. However, calcium chloride dissolution behaviour makes it difficult to be utilized well as desiccant. The first attempt to suppressdeliquescence behavior for dehumidification purpose was in 1976 where silt loam was usedas the host material. Further work has been presented to achieve the same goal using pure clay.The pollution effect of the spent bleaching earth (SBE) necessitated an investigation to determinewhether SHE could be used to eradicate the deliquescence behaviour of calcium chloride.The spent bleaching earth was purified to remove the entrained hydrocarbons through three steps; solvent extraction using hexane, oxidation of the hexane residues using 30% hydrogenperoxide and thermal oxidation. The ratio of 1 gram spent bleaching earth to 5 ml hexane and reactivation temperature of 550 DC in thermal oxidation were established as the optimalconditions for reactivation of spent bleaching earth. Hexane was found to remove about 25% of the entrained hydrocarbons mainly oil which was characterized. The results for the characterization indicated that the oil recovered could be utilized in non-food applications such as bio-lubricant, detergents, soap and other oleochemicals. Hydrogen peroxide removed about 10%of the remaining hydrocarbons after hexane extraction and thermal treatment about 5% after the two preceding steps. Laboratory studies were conducted to assess the mixing ratio of the inorganic salt, auxiliary binder and purified spent bleaching earth in the development of the composite adsorbent. Samples with different ratios were subjected to a humid environment of 88%relative humidity, by preparing a saturated solution of potassium chromate in a sealed beaker.The samples which recorded.minirnum surface wetting, spalling and cracking as well as high water uptake were further subjected to multiple sorption cycle tests. For all the tests performed, sample ratio of 3 :1 :0.25 of PSBE :CaCb :starch recorded the best results and was furthertested for its sorption properties at different relative humidity's. Sorption properties were carried out in a humidity chamber at 11.3, 32.78, 43.16, 52.89, 75.5 and 93.58% relative humidity where the sorption capacity recorded 14.88, 17.60, 20.95, 24.40, 33.40 and 45.55% water uptake respectively. The desiccant developed was found to be effective in high moisture content and thus viable in tropic regions where such environs are common. The sorption data obtained were subjected to the Langmuir, Freundlich and Brunaeur-Emmett- Teller (BET) adsorption models in order to determine the type of adsorption isotherm that best interpreted . water sorption by the material. Results indicated that, water adsorption onto adsorbent developed followed BET and Langmuir type III isotherm which indicated the formation of multilayer. The sorption capacity of the adsorbent matrix developed recorded 40 to 45% water uptake which cohered with commercially available desiccant such as silica gel. Since the SBE is normally disposed on potential land and limitations for this method of disposal is enormous, it is recommended that, oil manufacturing industries should emphasis on regenerating and re-using this waste in making products such as desiccants which they can use to preserve their products as well as sell to other consumers.
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    Characterization Of Snse-Cdo:Sn P-N Junction For Solar Cell Applications
    (2014-08-26) Nyakundi, Makori Evans
    Energy crisis occasioned by a decline in the availability of fossil fuels and increasing carbon dioxide emissions that are causing global warming has enhanced interest in the development of clean and renewable sources of energy. Solar energy has a great potential of meeting a large fraction of energy needs using photovoltaics. While most PV cells in use today are Silicon-based, cells of other semiconductor materials have been manufactured. Considerable research has been focused in search of thin-film PV cells with high conversion efficiency. In this study, SnSe and CdO:Sn thin films were optimised for photovoltaic applications. SnSe and CdO:Sn thin films were successfully deposited by thermal and reactive thermal evaporation respectively using Edward’s Auto 306 Magnetron Sputtering System . Their optical and electrical properties were studied using Solid Spec-3700 DUV Spectrophotometer and Keithley 2400 Source Meter respectively. Transmittance of the SnSe thin films deposited had transmittance ranging between 19-50% while reflectance ranged between 10-50%. The band gap values of SnSe thin films obtained were in the range of 1.71-1.76eV. SnSe thin films showed decrease of resistivity from 181-120Ωcm with increase in film thickness from 112-148nm. The optical properties of CdO:Sn showed high transparency in the visible region which varied with Sn doping, this makes CdO:Sn an excellent candidate for optoelectronic applications as a window layer. CdO and CdO:Sn had a transmittance of 70-85% and 50-89% respectively within the visible range of the electromagnetic spectrum. Reflectance of doped and undoped CdO was between 19-28%. Band gap energy for undoped CdO was 2.43eV while that of tin doped CdO ranged between 3.19-3.29eV for tin doping of 1-7%. Resistivity of CdO and CdO:Sn ranged between 16-93Ωcm. The optimised thin films were used to fabricate SnSe-CdO:Sn P-N junction. The I-V characteristics obtained were; Isc=0.993mA, Voc=273mV, Imax=0.905mA, Vmax=207mV, FF=0.69 and η = 0.59%.
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    Characterization, Evaluation and Performance Optimization of Wheat Straw – Bagasse Fuel Pellets
    (Kenyatta University, 2024-11) Matasyoh, Isabel Musula
    The current transition of the utilization of fossil fuels to sources of renewable energy has led to the exploitation of biomass energy from agricultural residues such as wheat straw and bagasse. The conversion of biomass waste into fuel pellets will provide an alternative source of reliable and affordable energy for cooking. This would help to curb the issue of over-dependence on fuel wood which results in deforestation. This research focused on the characterization, evaluation and performance optimization of wheat straw – bagasse fuel pellets. Wheat straw and bagasse were compacted to form fuel pellets. However, the fuel pellets could not be utilized directly before investigating their properties in order to determine their quality. The physical characteristics of the fuel pellets that were investigated included the moisture content, volatile matter, fixed carbon, ash content, calorific value, bulk density and mechanical durability. The effect of blend ratio, moisture content and raw material particle size on the ignition time, burning rate and specific fuel consumption of the wheat straw – bagasse blended fuel pellets was also studied. The water boiling test was used to determine the ignition time, burning rate and specific fuel consumption of the fuel pellets. This study involved varying four particle sizes (2 mm, 4 mm, 6 mm, 10 mm), four levels of moisture content (9.1%, 10.6%, 12.6%, 14.7%) and four blend ratios (10:90, 30:70, 70:30, 90:10). The results revealed that the fuel pellets with larger particles size, low moisture content and blends containing more bagasse had favorable burning characteristics. By using Response Surface Methodology, an optimization of the parameters was achieved. The results indicated that an optimum combination of blending ratio 10:90, moisture content of 14.70 % and a raw material particle size of 9.0481 mm resulted in the lowest ignition time of 38.001 seconds, highest burning rate 15.9511 g/min and lowest specific fuel consumption of 153.1153g/l. The findings of this work reveal that wheat straw – bagasse blended fuel pellets can be produced at optimal conditions by the use of optimization tools and practically utilized as a source of biomass energy.
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    Customers’ Perception of Mobile Banking and Financial Performance of Commercial Banks in Nairobi City, Kenya
    (Kenyatta University, 2023-11) Munyasia, Nelima Rose; Stephen Titus Waithaka
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    Demographic change and rural land use dynamics in Rongo, Migori County, Kenya
    (Kenyatta University, 2026-09) Mwai , Fredrick Nicholas
    Demographic change in most instances is considered the principal factor of human impact on land use change. The drivers of these changes, however, are dependent on the location, timeframe, and institutional design of the human environment prompting the changes to appear spontaneously or gradually. Agriculture for a long time has been the main development activity on most lands in Rongo Sub-County. However, in the last decade the area has been experiencing diverse development on its land posing numerous challenges such as uncontrolled development. It is in this view that this study analyzed the rural land use change trends in Rongo Sub-County between 2002 and 2022, examined the impact of population size on land use trends, and evaluated the influence of population socioeconomic status on trends in rural land use change in Rongo SubCounty. The Population and Environment Theory informed the conceptual framework and guided the study. The study site was purposively selected based on its rapid growth and visible land use transitions. A descriptive research design was adopted, allowing the use of both qualitative and quantitative data from primary sources including household survey questionnaires, field observation, key informant interviews, focus group discussions, and satellite imagery. Cluster random sampling was employed by dividing the population into locations where the required 384 households were randomly selected, while purposive sampling targeted key informants. Satellite images were downloaded from the United States Geographical Survey website and classified for the time interval between 2002 and 2022. The study adopted supervised classification where the area of interest was extracted. A review of relevant literature was undertaken to acquire secondary data. Arc Map 10.4.1 was used to analyze remotely sensed data, SPSS was employed for quantitative analysis, while qualitative data was analyzed thematically. Findings which were presented in tables and charts show that the study area’s population has increased by 45.5% over the study period (2002-2022) and that there is an increased number of households. Additionally, land area under rural agriculture extended constantly into forest lands between 2002 and 2022. The settlement area equally extended continuously into agricultural lands and forest lands, and wetland areas experienced minimal change. Majority with extra sources of income (45%) venture into other businesses thereby influencing the development of land. Agriculture is the main source of livelihood for the majority (43%) thus impacting the rate of demand for farmland. The study concludes that population size influences trends in land use change due to its impact on household number and consumption rate. Consequently, there is an expansion of farmlands for the production of food and a continuous increase of the area under settlements. Additionally, education attainment and access to extra sources of income impact the trend in rural land use change due to the efforts of the rural population towards the enhancement of livelihood. The trend in land use change in Rongo Sub-County involves the modification of forest land to farmlands and settlements. The study recommends training on sustainable approaches to maximizing farm yield, development, and implementation of policies that can influence the aspects associated with rural land use change transition tendencies.
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    Design and Fabrication of a Greenhouse Monitoring and Control System Based on Global System for Mobile Communication and Bluetooth
    (Kenyatta University, 2020) Nyaga, Stephen Gitonga
    Greenhouse technology should be embraced as a way of minimizing food insecurity in Kenya. The insecurity is brought about by climate uncertainties. Greenhouses have attempted to solve this problem by enclosing crops in a climatically controlled environment. Each greenhouse has distinct parameters. Data on these parameters need to be collected at regular intervals. Depending on the type of crop, these parameters need to be controlled within the specified limits to achieve the maximum efficiency and yields. In the past, greenhouses utilized electromechanical devices such as thermostats to monitor and control the environment. Mechanical systems lack the flexibility and precision required for greenhouse control. Some modern greenhouses use computers to control the environment. Computers based controllers are station based, bulky and costly. In this study a wireless prototype greenhouse monitoring and control system that is flexible, cheap, easy to maintain and easy to assemble was developed and implemented. The general objective of this research work was to design, fabricate and implement a microcontroller-based prototype to monitor and control greenhouse parameters using sensors, SMS technology and Bluetooth signals. The hardware consisted of ATmega328 microcontroller, Global System for Mobile communication (GSM) SIM800L module, HC05 Bluetooth module, HD44780U Liquid Crystal Display (LCD) module, 5 volt 4 channel relay module, Light dependent resistor (LDR) sensor and digital humidity and temperature (DHT11) sensor. The LDR sensor was utilized to measure light intensity while the DHT11 sensor was utilized to measure humidity and temperature levels in the prototype greenhouse. The DHT11 and LDR sensors, the relay, the LCD, the GSM and the Bluetooth modules were interfaced to the ATmega328 microcontroller. Through Arduino software, a program was written in C language, developed and uploaded to the ATmega328 microcontroller to run the greenhouse prototype. The program is designed to operate in automatic or manual mode. In automatic mode, the microcontroller constantly monitors the digitized values from the sensors and compares them with the optimized values and checks if any control procedures needs to be taken. In manual mode, the system could be operated wirelessly by use of GSM or Bluetooth module. The designed prototype greenhouse system is able to measure temperature, humidity and illuminance levels in the prototype greenhouse and display the values on the LCD. The system transmits the sensor measured values to owner’s phone via Bluetooth or a GSM and keeps these parameters at optimum levels by use of two fans, heater, bulb and a sprinkler. The GSM module is used for remotely monitoring and controlling the devices via a smart phone by sending and receiving Short Messaging Service via GSM network. If the user is in the vicinity of the prototype, the Bluetooth and a software installed in the smart phone provides a wireless link between the prototype and the cell phone. This project therefore provides a cost effective and efficient means of monitoring and controlling greenhouse parameters. In addition the system allows mobility during monitoring and control process. The reliability of the designed system can be exploited to build a network of such monitoring and control systems for several greenhouses. A website can be incorporated in the designed system to monitor the actual greenhouse values and save the data in an online database for future reference. The designed prototype greenhouse can be applied in the agricultural sector in the design and implementation of greenhouses.
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    Design and Optimization of a Solar Photovoltaic Mini-Grid: Case Study of Rwumba Village of Nyamasheke District, Rwanda
    (Kenyatta University, 2021) Augustin, Munyaneza; Maurice Kizito Wafula Mangoli; Keren Kaberere
    Universal access to clean energy is very paramount and brings along with it a lot of socio-economic benefits to the citizens in terms of poverty reduction, cost effectiveness and safeguarding the environment. However, most rural areas in developing countries have no access to electricity due to the high cost of power transmission and this hinders their development. In this perceptive, Rwumba Village of Nyamasheke district of Rwanda has no access to electricity from the grid. This research focused on the design of an optimum solar photovoltaic (PV) mini-grid system that can provide the required power and energy to the village. The solar PV mini-grid was designed and optimized using HOMER software. To achieve good results, two sites were visited and specific data were collected for each site by means of questionnaires. The first site visited is an existing standalone solar PV system known as Banda solar PV mini-grid and the second site is Rwumba village which is the case under study. The data collected from the existing Banda solar mini-grid include among others installed capacity and size of various system components, load data, energy and power requirements. Analysis of these data showed that this system is not optimum. The PV panels were found to be oversized whereas the storage batteries are undersized. Thus, using HOMER software, a model for optimizing this existing mini-grid was developed, simulated and validated using the data collected from the same mini-grid. The software simulated the combinations of inputs (PV panel, battery, power inverter and cost) at different capacity shortages and proposed the most optimum combinations. The best results corresponding to the optimum PV mini-grid were obtained at the capacity shortage of 3% which means that the mini-grid can meet the load at the reliability of 97% throughout the year. The estimated peak power and daily energy requirement was found to be about 7.5 kW and 51 kWh respectively. This is to be provided by PV panel capacity of 16 kW, battery bank storage of nominal capacity of 192 kWh that will be able to store energy for 3 days during cloudy days and power inverter of 12 kW. Then, the same procedure was followed to achieve most optimum results for Rwumba solar PV mini-grid. The optimum system size was found to have PV Panel capacity of 34 kW, a battery bank storage of 384 kWh nominal capacity, and power inverter of 15 kW serving an estimated daily load of 111 kWh. The power distribution system for the mini-grid was designed to be single phase supply two wire with distribution voltage of 230 V. The layout of households in the village dedicated the power to be distributed using three feeders from the power generation point. Feeder 1 is 0.4 km long, with power demand of 4.2 kW and a voltage drop of 4.5%; feeder 2 is 0.45 km long, power demand of 3.9 kW and voltage drop of 4.7% while feeder 3 is 0.45 km long, power demand of 5.9 kW and voltage drop of 4.4%. These results revealed that, the same size of the conductor present different voltage drop and power losses depending on the power demand and the location distance of the load being electrified from the generation plant. Economic analysis of the designed system was done using the life cycle cost technique. An annual interest rate of 6% and 20 years project life were used. The initial capital was found to be about USD 143,660. The payback period was found to be around 10 years at the system’s annual cash inflow of USD 13,435 and cost of energy of USD 0.419 per kWh. This means that there will be around 10 years of realizing the profit. Therefore, it was concluded that the project is financially feasible since the payback period is less than the project lifetime.
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    Design and Performance Evaluation of a Biomass Gasifier: Case Study of Coffee and Rice Husks
    (Kenyatta University, 2021) Mutuku, Kilaka; Thomas F. N. Thoruwa; Jeremiah Kiplagat
    About 36.1% of Kenya’s population lives below the poverty line. Low income has forced most of the Kenyans to opt for the cheapest available sources of energy. Biomass fuels are the most important source of energy in Kenya with wood-fuel (firewood and charcoal) accounting for over 68% of the total primary energy consumption. In spite of past efforts to promote substitutes for wood-fuel, the number of people relying on them is not decreasing. Consequently, it is projected that biomass will continue to be the main source of energy for the majority of the rural population and urban poor. Each year, over 2.8 million people in the world die prematurely from diseases caused by inhaling smoke from indoor fires due to incomplete combustion of biomass fuels in open fires and inefficient stoves. As a result of deforestation, biomass resources (fire wood and charcoal) are getting scarce. Waste products from agro-processing industries such as coffee husks, rice husks have been a major challenge in disposal. Biomass gasification is one of the few technologies that can potentially turn these wastes into energy for both industrial and domestic use. Although gasification has been around for more than 200 years, the technology is still new in Kenya. This study involved designing and developing a household-size biomass gasifier for the production of syngas using locally available biomass fuels namely; rice husks and coffee husks. Characterization of test fuels was based on their calorific value, percentage moisture content, volatile matter, ash content, fixed carbon, bulk density and porosity. Calorific value of rice husks and coffee husks was 15.9±0.8kJ/g and 18.1±0.8 kJ/g respectively. Bulk density of sampled rice husks and coffee husks was 127.4±1.2 kg/m3 and 218.0±1.6 kg/m3 respectively. Porosity of sampled rice husks and coffee husks was 87.4±0.9% and 71.9±0.6% respectively. Moisture content of sampled rice husks and coffee husks was 8.0±0.0% and 8.8±0.3% respectively. The percentage volatile matter of sampled rice husks and coffee husks was 62.8±0.3% and 78.4±0.0% respectively. The percentage ash content of sampled rice husks and coffee husks was 20.2±0.4% and 3.9±0.1 respectively. The percentage fixed carbon of sampled rice husks and coffee husks was 17.0±0.7% and 17.7±0.1% respectively. The maximum temperature obtained inside the gasifier reactor was mainly in the range 800°C to 1100°C. 1.5 liters of water at an average temperature of 24°C boiled in the stove within 4.7 to 8.5 minutes. Economic analysis of the gasifier found out that if a family shifts from LPG to using the constructed gasifier the payback period is 1.09 years, net benefit is Ksh45,000 (450USD) and rate of return on investment is 214.29%.
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    Design of a solar tracking concentrator system for process heat generation
    (2011-12-07) Githuku, Simon Mwangi
    In Kenya, biomass energy accounts for 75% of the energy consumed for domestic heating and industrial process applications. This has lead to massive deforestation and environmental degradation. In seeking solutions, this project was undertaken to develop a solar concentrating system for process heat generation in Kenya. The goal of the study was to design, construct and evaluate the thermal performance of the solar tracking concentrator for process heat generation. The solar tracking concentrator was designed, constructed and tested under field conditions in Kenya from February to August 2004. About 70 trials were conducted to investigate its thermal performance. The system components included rotating support structure, tracking unit with cylinders loaded with evaporative solvents, collector assembly (parabolic concentrator and receiver) and heat recovery unit. Locally available materials (including shock absorbers, solvents, square metal tubes & plywood) were used to construct the system. The measured parameters included solar radiation, ambient temperature, wind speed, tracking cylinders temperatures, water inlet and outlet temperatures, water flow, air inlet and outlet temperatures, airflow and tracking angle. The tracking unit utilized solvents for its operation. Three types of solvents used included chloroform, carbon tetrachloride and methylated spirit. The tracking angle was read and recorded manually at a regular interval of 10 minutes. Average process temperature ranging between 41.8 ± 9.7°Cand 59.3 ± 147.7°C was generated with an average insolation of 665 ± 302.1 W/m2 and 684.4 ±147.7 W/m2 for the non-tracking and the solar tracking systems respectively. From 70 field tests conducted in Kenya with system loaded with methylated spirit, chloroform and carbon tetrachloride the following was concluded: (a) Chloroform solvent with an average tracking accuracy of 82+13.2% proved to be better than that of carbon tetrachloride that had tracking accuracy of 74.1± 2.5%. (b) The use of mirrors on the solar concentrator's surface and integration of a solar tracking system increased the thermal efficiency by an average of 9.0 ± 1.5%. (c) Concentrating system loaded with chloroform showed potential to generate 82.5± 5kWh per day when operating with averaged solar radiation of 644.3 ± 30.5 kW/m2. (d) The solar tracking concentrator loaded with chloroform solvent demonstrated great potential for use in process heat generation, industrial and agricultural drying operations in sunny countries.
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    Determinants of Knowledge Sharing Through Institutional Repositories among Academic Staff in Selected Public and Private Universities in Kenya
    (Kenyatta University, 2025-10) Njogu, Lynette Wambui
    In recent times, organizations have experienced changes that have been characterized by the shift from relying on information to the utilization of knowledge. This led to the birth of the Knowledge Management (KM). With organizations investing in embedding KM in their operations, a component of KM being implemented is knowledge sharing. In this study, Knowledge Sharing (KS) is the process by which knowledge generated and stored in an organization is communicated from the source to the recipient. Universities have not been left behind in implementing KS by facilitating their academic staff in this endeavour. They have invested in ICT platforms where respective academic staff share knowledge generated and gained through research. The ICT platforms residing in institutions are referred to as Institutional Repositories (IRs). An evaluation of a number of university institutional repositories, show that academic staff in some faculties have contributed more research and knowledge outputs, while others have little or no contributions. This study led to establishing what determines academic staff’s decision to share their research and knowledge outputs via institutional repositories in selected universities in Kenya. The research objectives that guided the study included: establishing ICT skills of academic staff, the provision of a university ICT policy on knowledge sharing through institutional repositories, the perception of academic staff members in knowledge sharing and the reward systems for knowledge sharing through IRs. This study adopted the Knowledge-Sharing model developed by Cheng et.al. in 2009 as its theoretical model. Descriptive research design was adopted for the study. The study location for the research was the University of Embu, a public university, and St Paul’s University, a private university. The target population in the selected universities was 151 academic staff. A questionnaire was used as the data collection tool. Qualitative data was analysed based on the themes of the study. Descriptive statistics were used to analyse quantitative data and were presented through frequencies, percentages, tables, and graphs. The study major findings included; the academic staff members have a positive perception on knowledge sharing through IRs, self-archiving of knowledge and research outputs through IRs is yet to be embraced, academic staff are not aware if KS through IRs is included in their respective university ICT policy and the academic staff are not satisfied with rewards system in place for awarding knowledge sharing through IRs and suggested monetary and non-monetary rewards as measures to improve on the reward systems. The study recommended that academic staff to be facilitated on self-archiving of their knowledge and research outputs via Irs. Also, universities to include and discuss KS through institutional repositories in their respective ICT policies, conduct user education to academic staff on KS through institutional repositories issues that are discussed in their ICT policies and to evaluate and improve on the rewards system that the respective universities have established.