Department of Computer Engineering and Informatics
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Item Digital forensics framework for ensuring integrity and traceability of AI-based medical imaging : case study, breast cancer imaging data.(Busitema University, 2026) Omiel, LukasBreast cancer remains a serious worldwide health challenge and one of the leading causes of death in females. While Artificial Intelligence (AI) based medical imaging supports early disease detection, its reliability is currently compromised by lack of mechanisms to validate the integrity and traceability of images processed within the AI pipelines. This study addresses these issues by integrating cryptographic watermarking and hashing mechanism in a forensic by-design framework that performs AI-based medical image classification. The proposed framework performs content and context tamper detection as well as image classification through transfer learning using a pretrained Resnet50 Convolutional Neural Network (CNN). With a Peak Signal-to-Noise Ratio (PSNR) of 52.71 dB and a Structural Similarity Index (SSIM) of 0.9997, forensic evaluation shows that the framework guarantees tamper detection without affecting diagnostic quality. The maximum Integrity Detection Rate (IDR) of 100% was attained by the security layer alert, which also had the lowest False Acceptance Rate (FAR) and False Rejection Rate (FRR) of 0%. Additionally, the findings of the experiment show a classification performance with an accuracy of 91%, a high Area Under the Curve (AUC) of 96.4%, and a benign recall of 94%, providing sensitivity in recognizing tissue that is not malignant. These findings show resilience to integrity violations during image classification. In contexts with limited resources, our hybrid method ensures that diagnostic data is authentic from the time of capture to the final clinical decision by providing the required foundation for AI forensics.Item Forensic framework for insider threat detection and mitigation in corporate networks.(Busitema University, 2026) Kakaire, GodfreyInsider threats present severe risks to corporate networks due to the authorized access privileges and contextual knowledge of internal users. This study designed and evaluated an integrated, proactive forensic framework using Design Science Research Methodology (DSRM) to enhance early threat detection and mitigation in Ugandan corporate networks focusing on banking, fintech and telecommunications sectors. The proposed framework integrates User and Entity Behavior Analytics (UEBA), real-time monitoring and automated response orchestration using open-source technologies including Wazuh, Elastic Stack, Apache Kafka and custom machine learning models (Isolation Forest, Autoencoder, and Long Short-Term Memory). The framework was evaluated using a multimethod strategy including expert Delphi review, controlled laboratory simulations and a quasiexperimental field study across twelve corporate environments. Expert review achieved strong consensus on design feasibility and forensic readiness (Cronbach’s alpha = 0.89). In controlled simulations, the proposed framework achieved a 91.5% detection rate compared with 67.3% for the rule-based SIEM baseline, reducing Mean Time to Detect (MTTD) from 47.2 to 8.3 minutes and lowering the false positive rate from 34.2% to 12.8%. The field observations during a three-month post-intervention period (April–June 2026) showed shorter containment times with Mean Time to Contain (MTTC) recorded at 18.7 hours compared to a literature-derived baseline of 96.3 hours. These findings demonstrate that integrating behavioral analytics and automated containment can improve threat detection, incident response and forensic readiness in resource-constrained corporate networks without the high costs of proprietary solutions.Item Classification of criminal activities in surveillance footage using human detection and temporal sequence modeling.(Busitema University, 2026) Namuyomba, Angella ZeridaManual reviewing of surveillance footage to retrieve the evidence is a tiresome and time consuming activity due to the scarcity of frames containing these evidences. This study explores a framework for modeling spatial-temporal features to classify criminal activity in surveillance footage. This study proposes an approach that investigates the use of spatial features derived from YOLOv8 person detections as sequential representations of human behavior for LSTM-based crime classification in surveillance footage. We utilize deep learning object detection algorithms and Recurrent Neural Networks (RNNs) to learn the spatial-temporal features extracted from the UCF crime dataset in order to classify criminal activity in surveillance footage. Object detection allows us to focus our attention on frames that contain humans and human activity to avoid searching through empty frames. We believe that since most, if not all crimes involve human activity, it’s imperative to accurately detect people in the challenging surveillance footage. A comparative study was carried out to assess the performance of the common deep learning object detection tools i.e single shot mult-ibox detector (SSD) and you only look once version 8 (YOLOv8) in detection of humans in challenging surveillance footage. The dataset used for this study was compiled from the HR crime dataset which consists of 13 categories of crimes that are Abuse, Arrest, Arson, Assault, Road Accident, Burglary, Explosion, Fighting, Robbery,Shooting, Stealing, Shoplifting and Vandalism. The study indicated that the YOLOv8 object detection tool outperforms the SSD detector with a mean average precision (mAP) of 0.97 and intersection over union(IOU) of 0.89. The obtained bounding box information together with the confidence scores is converted into sequences which are then used to train and evaluate an LSTM model. The model attained an accuracy of 0.8091, F1 score of 0.8099 and MCC of 0.7919.. This implies that the model ably classfies the criminal activity in the surveillance footage and can facilitate users in faster acquisition of criminal evidence with minimal human supervisionItem A mobile-based digital notice board system for real-time dissemination of university (BU digital notice board).(Busitema University, 2026) Moko, Julius; Cheptegei, LabanThis project report presents the design, development, and evaluation of the BU Digital Notice Board, a mobile-based system developed to improve the dissemination of official university notices at Busitema University. The project was motivated by the limitations of physical notice boards and informal communication channels such as WhatsApp groups, which often result in delayed updates, message loss, misinformation, and limited access to official notices. The system was developed using Flutter for the mobile application interface and Firebase services, including Firebase Authentication, Cloud Firestore, Firebase Storage, and Firebase Cloud Messaging, for backend support. The application provides user authentication, role-based access control, categorized notice posting, multimedia notice support, offline access to cached notices, push notifications, and dedicated portals for guild, cultural, and religious communities. The system was evaluated through unit testing, integration testing, and user acceptance testing with selected users from the Faculty of Engineering and Technology. Results showed that the application improved the timeliness, accessibility, and reliability of notice dissemination compared to physical notice boards and informal social media groups. The project demonstrates the potential of mobile-based systems in enhancing institutional communication within university environments. Keywords: Mobile application, Digital notice board, Real-time communication, Firebase, Flutter, Offline-first, Push notifications, Busitema University.Item An Iot-driven patient vital monitoring and doctor alerting system for early health intervention.(Busitema University, 2026) Turinawe, Richard; Nabirye, Barbra BayuuleAccess to timely health monitoring is limited in rural areas like Busia District, where patients with chronic conditions often face delays in diagnosis and treatment due to limited medical personnel, lack of diagnostic equipment, and unreliable internet connectivity. This project aims to develop a low-cost, IoT-driven wearable device capable of continuously monitoring essential vital signs, including heart rate, oxygen saturation (SpO₂), blood pressure and the body temperature. The system incorporates a real-time alert mechanism that notifies doctors or caregivers when abnormal readings occur, ensuring prompt intervention. Requirements for the system were identified through stakeholder consultations and literature review. A prototype wearable device was designed and integrated with Wi-Fi connectivity to support both online and offline operation, addressing rural infrastructure challenges. Field validation was conducted in local healthcare settings to evaluate accuracy, usability, and reliability. Results indicate that the device can effectively monitor patient vitals, provide timely alerts, and operate sustainably in low-resource environments. This system offers a practical solution to improve patient care, reduce preventable complications, and enhance health outcomes in rural communities.Item Automated hydroponic fodder growth chamber with live monitoring and AI mold detection.(Busitema University, 2026-07) Kabwangu, Muhamed; Talemwa, DicksonLivestock production heavily depends on the consistent availability of high quality fodder and hydroponic fodder systems have become a sustainable solution for efficient animal feed production. However, these systems are often affected by challenges such as mold contamination and the lack of continuous monitoring, which can reduce fodder quality and result in losses. Traditional manual inspection methods are time consuming, inconsistent and unable to provide real-time monitoring of system conditions. [1] This project presents the design and implementation of an Automated Hydroponic Fodder Grow Chamber with AI-Based Mold Detection and Real-Time Web Monitoring System to address these challenges. The system automates the monitoring of key environmental parameters such as temperature, humidity and pH level using sensors connected to a microcontroller. A camera-based Artificial Intelligence model was integrated to detect mold growth on hydroponically produced rice fodder. The AI model processes images frames using computer vision techniques and classifies the fodder as either healthy or mold-infected. The results are displayed in real time on a web-based dashboard together with sensor data for easy monitoring. The integration of automation, artificial intelligence and web technologies enables continuous monitoring, reduces manual inspection efforts and improves the accuracy and speed of detecting mold contamination. This leads to improved fodder quality, reduced losses and more efficient livestock feed production.Item ICT policy for the disabled in offing.(New Vision, 2017-11-01) Kasanga, KyetumeInformation and Communication Technologies (ICTs) have become the leading medium for communicating, transacting, informing, education and entertaining all over the world. Usage of technologies such as television, radio, fixed and mobile telephony,Item ICT graduands warned against misuse of the media.(New Vision, 2017-09-11) Odeke, FaustineOver 200 participants who attended a two-week information communication technology (ICT) training have been cautioned against the misuse of media platforms. The training, which was organised by the ICT ministry and held at Asinge Senior Secondary School in Tororo district, attracted a large number of participants and some were turned away due to limited computers and space.Item Technology linking Karamoja to services(New Vision, 2018-06-01) Mulondo, LawrencePastoralists are trained in the use of social media platforms, such as WhatsApp and Facebook. They are embracing technology to connect with veterinary doctors, district leaders and security officers in case of emergencies.Item Biotechnology law a welcome devt.(Daily Monitor, 2017-10-30) Nyanzi, Timothy JosephAfter several years of activism, consultative meetings and nationwide sensitisation of both policy makers and the public, the National Biotechnology and Biosafety Bill 2012 has finally been passed into law- the National Biosafety Act 2017. This is a great milestone for Uganda as a nation,Item Why cyber labs can never replace traditional practicals(New Vision, 2017-08-02) Nakajubi, GloriaGloria Nakajubi explores the effectiveness of cyber labs as alternative to hazardous chemicals used in science experiments.Item Smart jackets detects pneumonia faster(Sunday Vision, 2017-07-30) Affedda, EmmanuelA group led by Brian Turyabagye has created a jacket-like device named 'mama ope'. The jacket helps detect pneumonia early in order to facilitate quick life-saving treatment.Item Government to buy local ICT innovations- Rugunda(New Vision, 2017-08-02) Kayiwa, EdwardPrime Minister Dr Ruhakana Rugunda has said the Government will purchase ICT applications that are created locally in its bid to improve service delivery ahead of the vision 2020. "We should develop and adopt ICTs for smarter cities, education, environment, agriculture, healthcare and commerce." Rugunda.Item Shs80m innovation hub unveiled at Makerere(Daily Monitor, 2017-10-11) Kasemiire, ChristineAn innovation hub for the youth that will boost new technology creations has been unveiled at Makerere University.Item Schools, hospitals to get biometric machines(New Vision, 2018-05-18) Kakamwa, CharlesThe Government is set to introduce biometric machines at schools and health facilities to monitor staff attendance, in an attempt to reduce absenteeism.Item Free Internet:(Daily Monitor, 2017-10-27) Draku, FranklinWhen the government, through the National Information Technology Authority Uganda (NITA-U), commissioned its much hyped free internet services in Kampala Central Business district and some parts of Entebbe in September last year, the move was received with enthusiasm.Item Technology firms push for QR code payments.(New Vision, 2017-09-09) Kulabako, FaridahUganda's pursuit for a cashless economy may soon be given a boost after Visa, a globe payments technology firm, announced support for Quick Response (QR) code payment specifications. QR is a global system that seeks to promote mobile commerce and e-payments.Item Machines to track absentee teachers, medics acquired(New Vision, 2018-05-23) Mubiru, ApolloThe Government has acquired Biometric machines to capture arrival and departure times for health workers in 221 health facilities in eastern Uganda.Item Students develop a light sensor to save energy(Sunday Vision, 2018-04-22) Ssenyonga, AndrewTwo Information and communications Technology students from St Kizito High School Namugongo in Kira Municipality, Wakiso District, have developed a light sensor to automatically control domestic and commercial electricity usage to save energy. The device, uses an auto energy saving system controlling lighting through a detractor that switches Off the lights during day and On when its dark.Item Social media mistakes that will ruin your career.(Daily Monitor, 2017-10-02) Atangaza, B CarolyneAnthropologist and Makerere University Research fellow Dr. Stella Nyanzi's recent troubles with the law is a clear example of how dangerous social media can be. With her humour and bawdy descriptive language, the professor had followers hanging onto every post.