School of Computing and Informatics Technology Collection
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ItemTracking management information system for EEMS(Makerere University, 2022)Main Objectives: To develop a Management Information System for EEMIS that will handle tracking of the workers sent abroad by different approved export companies and monitored by the relevant authorities. Specific Objectives: 1. To identify requirements that will be used in the development of the system. 2. To design a web-based system for tracking at EEMIS Uganda. 3. To implement the designed system. 4. To test and validate the implemented system.
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ItemAn online appointment management system for Mengo Hospital(Makerere University, 2023)With the enhancement in technology, so many aspects in different fields are also embracing and advancing in new technology. We managed to work on a system that automates the visitor's appointment management process in hospitals, identifying our case study as Mengo hospital Uganda. This hospital already has a manual system in place which records visitors information manually, and with this kind of operation, of course we expect so many vulnerabilities here and there not forgetting inefficiencies. The purpose of this research proposal is to deliver an online appointment management system for hospitals like Mengo, and this proposed system will enhance building security, improve visitor experience, and effectively monitor, track, and record visitor information. In order to achieve the above objectives, our system is exclusively enhanced with features such as pre-registration, contactless check-in, real-time monitoring and tracking, advanced security features including health screening measures.
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ItemInterpretable foot and mouth disease detection(Makerere University, 2025)Foot and Mouth Disease (FMD) is a highly contagious viral infection that hinderslivestock production, resulting in severe economic losses in Uganda[21]. This study investigates an interpretable machine learning approach to FMD detection by using two distinct datasets: a numerical dataset sourced from Uganda for early detection, and an image based dataset collected from the internet for visual diagnosis. Exploratory Data Analysis (EDA) was conducted to assess feature distributions, identify class imbalances, and uncover correlations among epidemiological and environmental factors such as rainfall, temperature, livestock density, and geographic proximity to national parks and borders[5]. A total of six models were developed—four trained on the numerical dataset and two on the image dataset. For early detection, models including Random Forest, Support Vector Machine (SVM), Logistic Regression, and Gradient Boosting were evaluated. The XGBoost model, when combined with the Synthetic Minority Oversampling Technique (SMOTE), achieved the highest accuracy of 82%. However, performance decreased in scenarios involving dynamic or imbalanced data distributions, underscoring the need for adaptive learning strategies.[15] In the image-based classification task, deep learning models comprising a custom Convolutional Neural Network (CNN) and ResNet50 were implemented. Among these, ResNet50 achieved the highest accuracy of 97%, demonstrating strong potential for visual FMD symptom detection. To enhance transparency and model trustworthiness, SHAP was employed to explain feature importance in numerical models, while Grad-CAM was used to generate class activation maps for CNN-based image models[14]. This report emphasizes the value of integrating explainable artificial intelligence (XAI) and adaptive machine learning in livestock disease diagnostics. The proposed approach provides a foundation for developing robust, data-driven decision support systems to strengthen early warning and surveillance mechanisms for FMD in Uganda.
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ItemMobile-based poultry product sales and marketing application (MPPSAMA)( 2024)Poultry farming, a critical component of Uganda's agricultural sector, significantly contributes to economic development and food security. Despite its importance, the poultry industry faces challenges, including inefficient market coordination and limited access to profitable markets. This study proposes the development of a Mobile-Based Poultry Product Sales and Marketing Application (MPPSAMA) designed to address these challenges by connecting farmers directly with buyers, providing real-time market information, and streamlining the sales process. The research adopted stratified sampling to gather data from poultry farmers and buyers in the Kampala and Wakiso regions. Data collection methods included interviews and questionnaires, enabling the collection of comprehensive insights into the current marketing practices, challenges, and user preferences for a mobile-based solution. The Agile System Development Life Cycle (SDLC) was employed to develop the application, ensuring a user-centric and iterative approach. The literature review highlights the significance of poultry farming in Uganda and the potential of digital solutions to enhance market efficiency. It also underscores the challenges of technology adoption in rural areas due to limited internet access and inadequate infrastructure. The study's findings emphasize the need for a centralized platform to improve market coordination, reduce product waste, and increase profitability for farmers. The mobile application aims to bridge the gap between poultry farmers and buyers, providing a reliable and efficient platform for marketing poultry products. By leveraging technology, the application seeks to transform the poultry sector in Uganda, promoting sustainable growth and enhancing food security. The study concludes that the successful implementation of this digital solution can significantly impact the livelihoods of poultry farmers and contribute to the overall development of the poultry industry in Uganda.
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ItemFire fighting system : embedded system(Makerere University, 2017)In the world today, firefighting is one of first priorities to any country or government for its survival. Fire outbreak is one of the biggest setbacks due to the enormous losses associated with it, the losses can be property or lives or monetary. In well developed countries, for example the United States, China and several European countries, etc. there exist advanced mechanisms of firefighting like, AFT portable water mist and CAFS systems. These give fire fighters a bigger advantage in the fight against fire. However, in low developed countries like Uganda and many African countries, without the above mentioned firefighting mechanisms, firefighting is very difficult and a very big challenge to these countries. Given the fact that they have gotten poor infrastructure i.e., Poor road networks for the movement of the fire brigade trucks to places that have caught fire, poor communication means of network, without advanced firefighting tools fire accidents remain a big problem to many places of these countries. Firefighting system is an embedded system with GSM capabilities that uses sensors like the smoke detectors and fire sensors to detect fire, activate an alarm and also set off the water sprinklers of the building and then send a message to the nearby fire brigade department and other people responsible like the local authorities to rapidly respond, the message contains the location of the building, the time the fire started, how to switch off the system and an option to forward the message to different people. The system sends a message every after six hours to responsible people to counter reliability. The system automatically goes off when the temperature reduces to ‘normal’.