ghanaopendata/ghanaian-research-english huggingface dataset:
Design of wearable motion data capture system for athletic biomechanical analysis

Application of biomechanics in athletics aids the optimization of performance and effective prevention of injury in athletes. However, there are several barriers that lie in the way of further integration of biomechanical analysis in the sport, especially regarding infield performance of athletes. Developing areas of the world are also left out of the benefits since their coaches and athletes do not have access to the laboratories that house the technology used for the capture and analysis of biomechanical data. This project seeks to design and build a prototype of a low-cost, accessible, wearable motion capture system for use in in-field motion data capture to generate information that coaches, and athletes can track to enhance performance and reduce risk of injury. The specific biomechanical factors, kinematic and spatiotemporal factors needed will be investigated, and sensors capable of measuring them will be selected and used to design the system. The interface of the project will be designed based on the requirements selected within the context of the training and competition environment to enable coaches and athletes utilize the system effectively.

Source: Ashesi
Design, implementation and testing of a non-intrusive malaria sensor

Malaria is a primary factor affecting morbidity and mortality worldwide especially in tropical countries [1]. There are three tests recognized by the World Health Organization for the diagnosis of malaria: Rapid Diagnostic Test, Clinical Diagnosis, and Microscopic. Test. The Microscopic Test and the Rapid Diagnostic Tests are invasive methods diagnosis where your skin is pricked for blood samples. The Clinical diagnostic Test is mostly inaccurate because it is based on the doctor s discretion This project seeks to explore a non-invasive (non-intrusive) method of diagnosis which leverages on the idea of fever patterns of a malaria patient following a common pattern to digitally diagnose a patient by taking their data over a period (in this case one to two days). This was done using Fast Fourier Transform to extract the frequencies of the fever signal and running these frequency components through a machine learning algorithm. The algorithm that was for this project was the Naïve bayes classification algorithm giving us an accuracy of 82.61% and a recall of 100%.

Source: Ashesi
Designing a computer numerical control farming system for local homes

This project explores the idea of using the principle of Computer Numerical Control(CNC) to build a farm machine. The project can be divided into three facets. The first involves the mechanical component of the machine. Building the farm and assembling and mounting the motors that would be used for movement. The second part is heavily based on electrical work. Connecting sensors, and motors and fixing the communication bit for the machine. The final part is the computerized part. This part involves communication of the machine with a server to provide the user with up to date information where ever they are.

Source: Ashesi
Designing a low-cost solution for guitarists in Ghana who cannot afford to import effect pedals

Music is a very important part of the Ghanaian society and it serves many purposes. In more recent times, the guitar has been one of the most widely used melodic instruments in music production. With the invention of the effect pedal, guitarists worldwide have been able to use a wider variety of tones to produce more complex and enjoyable music. In Ghana, however, these pedals need to be imported and this prevents a lot of guitarists from having a lot of tones to choose from which impedes their craft primarily because the cost of the pedal increases significantly while access to the pedal locally is restricted. Often software implementations of the effect pedals are used as substitutes for their hardware counterparts, but this comes at a cost of the reduction in tone quality. In this project, a low-cost effect pedal is designed and built to suit the needs of guitarists who cannot afford imported effect pedals.

Source: Ashesi
Designing a mimic of Ashesi Courseware that Integrates peer learning techniques

This projects seeks to expand the usage of peer learning in tertiary educational institutions. It focuses on designing and a developing a simplified mimic of the Ashesi Courseware that shall make use of peer learning techniques. This is done by granting both lecturers and students the permission to share coursework materials they feel relevant to a given course. It also includes extending its uses to allowing students to give feedback on the usefulness of materials shared in understanding class concepts and the recommendation of materials to students through the rating of uploaded materials. The result is a sharing application that has the potential to be a vibrant information sharing platform.

Source: Ashesi
Designing an Affordable Semi-Active EMG-Controlled Prosthetic Arm For Amputees in Ghana

The high cost and limited accessibility of advanced prosthetic devices pose a significant challenge to upper-limb amputees in low-income regions. This project investigates how a low-cost, active prosthetic arm can be developed using electromyography (EMG) signals to restore essential hand functions for individuals with after-the-elbow amputations. The objective is to create an affordable, intuitive, and reliable prosthetic solution that responds to real-time muscle activity. Situated at the intersection of biomedical engineering, mechatronics and inclusive design, this research addresses a critical gap in assistive technologies for underserved populations. The methodology integrates hardware and software systems across four core subsystems: EMG signal acquisition and classification, wireless communication, actuation, and mechanical design. EMG signals are captured using sensors around the forearm and processed via a machine learning model to classify gestures such as gripping, releasing, and resting. The classified gestures are used by a Raspberry Pi 5, which drives motor responses in the prosthetic hand. A spring-mass-damper model is applied to simulate finger dynamics, enhancing the accuracy and ensure the responsiveness of the system. By collaborating with a local prosthetics manufacturer, the design was refined to meet practical needs including weight, usability, and functionality. The model selected was a hybrid CNN-LSTM architecture and it managed to produce a training accuracy of 84.38% and a real-time testing accuracy of approximately 75%. This project demonstrates that meaningful, low-cost prosthetic innovation is possible using accessible technologies. Its potential impact lies in expanding mobility and independence for amputees in resource-constrained settings, while offering a scalable framework for future research in affordable biomedical devices.

Source: Ashesi
Designing an Automatic Water Pump for Household and Small Scale Industries

Water plays an important role in our daily lives and also the scarcity of it increasing. Most countries in Africa are facing this kind of problem. Most countries in Africa are facing this kind of problem due to mismanagement and a high illiteracy rate. People are mostly busy and ignorant that they forget to turn off the pump motor when the overhead tank is full. The overhead tank then overflows. Water and power are wasted in this process. This paper presents a solution to this problem. An automatic water pump system is designed to monitor the water level of the water tank and turn the pump on and off due to the water pump level. Also, a water level indicator is built to show the status of the tank to the user. The system consists of three sensors. Two of the sensors are placed at the maximum and minimum levels, respectively. When the sensor does not touch the water at the minimum level, the pump turns ON and turns OFF when the water touches the sensor at the maximum level. The system consists of a CD4001BP which performs the logical operation for the pump to turn ON and OFF.

Source: Ashesi
Designing And Construction Of Low-Cost Biochar Production Unit

This project focuses on designing and constructing low-cost biochar production units for small scale farmers. It aims to provide an affordable and efficient solution, which is using biochar as fertilizers, to farmers whose yields are affected by low soil fertility. Biochar is produced from a pyrolysis process, which occurs at temperatures ranging from 200 to 500 degrees Celsius, and this product offers significant benefits for soil improvement, carbon sequestration, and sustainable growth. The project's main objective was to develop a functional unit from locally available materials to produce biochar from agricultural waste. The final design features were a pyrolysis reactor, condensation system, and the collection bottle. While testing the unit's performance, it was operated at 200 to 300 degrees Celsius over a 4-hour period, yielding about 1.5 kg of biochar and 0.5 kg of vinegar (bio-oil). After obtaining the biochar was tested on Loam soil to see how it affects its capacity to hold water. The test used the two-biochar produced from maize cobs, coconut shells, and only soil. The One-Way ANOVA test results were used to test the significant effect among the three samples, where a p-value was less than 0.05 [ F (2, 6) = 5.687, P=0.0412], indicating that they significantly affect the soil's water retention capacity. In addition, this project indicates potential for low-cost biochar production units to support sustainable agriculture practices and other applications of the obtained byproducts, such as vinegar, which can be used as a pesticide. Therefore, this contributes to better agricultural practices and food security.

Source: Ashesi
Designing and implementing a rural ICT center

This report details the findings of an applied project to design and implement a sustainable Information and Communications Technology center in the rural community of Berekuso. The project was intended to address the challenges of providing the community with access to quality education. The project design was divided into three key areas which include the establishment of the physical hardware infrastructure, the hosting of a digital library equipped with relevant educational content, and ICT literacy and training services. The implementation of the project consisted of two phases, the first of which is the initial setup phase and has been fully implemented. The second phase involves long-term support and is yet to be implemented. This report is concerned primarily with the first phase, although some recommendations have been made concerning the implementation of the second phase and beyond.

Source: Ashesi
Designing augmentative and alternative communication systems that focus on real-world contexts as well as the motor, cognitive and linguistic processing of autistic children

Children with autism spectrum disorder (ASD) require Augmentative and Alternative Communication (AAC) Systems to be able to communicate their feelings, thoughts, and expressions. However, AAC systems are not being developed to focus on the complex communication needs of individuals such as the motor, cognitive , sensory needs of the users of the system. Without a focus on the complex and varying competencies of the users of the system, the technology does not perform its intended role of enhancing communication but rather places a cognitive load on the users. In this project, guidelines, and recommendations for developing a tablet-based AAC application that satisfies the complex needs of autistic children with a different ASD diagnosis would be provided. The study analyzed the user interface of Eline Speaks, a tablet based AAC system and identified the limitations, accessibility and usability issues of the system. Recommendations on developing an accessible AAC system was derived from testing a high fidelity prototype in comparison to that of Eline Speaks, an already existing system.

Source: Ashesi
Designing wearable obstacle detection and avoidance technology for the visually-impaired

Assistive technology for the visually impaired is developed regularly, but many of these solutions are either bulky, difficult to maneuver, or expensive. Visually impaired people need a way to avoid obstacles and move around in safety. Due to limited visibility, the person cannot tell with confidence if there is an obstacle approaching them. This project proposes a wearable obstacle and avoidance system for the visually impaired housed on an embedded microcontroller. The system consists of both RFID and sonar localization techniques for static and dynamic obstacles. Both approaches work well in terms of obstacle detection and avoidance, but further research is needed to integrate the processes to complement each other fully. A simultaneous localization and mapping (SLAM) approach, though computationally expensive, is also considered. The results show that it is possible to combine both RFID and sonar localization; however, this approach might be better suited for a less constrained system.

Source: Ashesi
Detection and Billing of Taxable Building Properties in Ghana: A Satellite-Based Approach

The rise in the number of a nation's physical infrastructure is a key indicator of its development and, likewise, the proceeds from taxable infrastructure. However, in many sub-Saharan African countries (for example, Ghana), the amount of taxes realised from such infrastructure as buildings (property rates) fall short of expectation and hence hamper national development due to delays in the detection of such properties as well as logistical challenges. Therefore, the importance of accurate and timely detection and billing of such properties cannot be overemphasised. This work sought to evaluate and enhance the performance of some state-of-the-art segmentation models for building detection (U-Net, FPN, PSPNet, U-Net++, LinkNet and MAnet), primarily focusing on satellite images of Berekuso in the Akuapem South Municipal Area. Initial analysis showed that the U-Net++ outperformed the others on the Massachusetts Building Dataset (IOU = 0.8280, mean dice loss = 0.1241, precision = 0.8856, recall = 0.9260, F1 score = 0.9054, and accuracy = 0.9077) but achieved a lower accuracy on the Berekuso Dataset. However, a significant increase in performance is observed by combining enhanced (histogram equalisation) satellite images with post-training techniques. The study, therefore, proposes an incentivised billing system based on the above enhancement mechanism with U-NET++ for building detection towards climate sustainability. This study aligns well with the sustainability goals of SDG 11, 13 and 15.

Source: Ashesi
Detection, classification and mitigation of power quality disturbances on the Ashesi University L.V. distribution network

This paper seeks to provide a system for ensuring quality power supply at Ashesi University. The system would be based on ESP32 MCU board, and capable of measuring electrical power supply quantities and also offering protection against sustained power interruption, overvoltage, and undervoltage to the valuable power electronic equipment at the school. The hardware setup is capable of offering protection to 3-phase loads in real time. Throughout this paper, the hardware and software setup is emphasized and analyzed in detail, in-terms of specific components used such as the PZEM-004T from which the parameters are read using the ESP32 as well as firebase- which was used to design the database and host the web application. On top of reading the values, ESP32 is utilized for logging the data onto firebase real-time database through the inbuilt Wi-Fi module, for visualization of the data. RMS voltage and current, active power and power factor are closely monitored in comparison with the IEEE standards to help determine opening and closure of the relay module in-case of detrimental power disturbances. The system was able to read and log the data into an online database, and analysis of these readings in line with the set standards indicated proper operation of the system.

Source: Ashesi
Determination of power consumption of a machine learning algorithm sunning on a microcontroller

Machine learning (ML) inference is now common on low-end microcontrollers. This presents various advantages, such as real-time decision-making at the edge where sensors are located. However, power consumption arises as the main challenge to low-end microcontrollers, which fail to prolong the battery life due to the execution of machine learning inference. This project investigates the power consumption of a machine learning algorithm running on a microcontroller unit (MCU) in order to provide the embedded ML designer with insights into software and hardware optimizations. This work focuses on the power consumption of two machine learning algorithms (support vector machines and artifical neural networks) and their implementation on KL25Z (ARM Cortex-M0+) and K64F (ARM Cortex-M4) using standard libraries provided by ARM CMSIS (CMSIS-DSP and CMSIS-NN), and custom-developed functions. The results showed that there was a significant power saving by implementing machine algorithms in Cortex-M4 with CMSIS libraries, while in Cortex-M0+, power efficiency was achieved through custom implementation of ML algorithms. In conclusion, for MCUs with hardware accelerators such as the floating-point unit (FPU) or support for Single Instruction Multiple Data (SIMD), CMSIS implementation of ML algorithm tends to be more power efficient, while for MCUs without the support of FPU and SIMD, custom implementation of ML algorithms tends to be more power efficient.

Source: Ashesi
Determining the best load scheduling algorithm for a home with electricity supply from grid and solar

Іmprοvіng еnеrgy еffіcіеncy іs bеcοmіng іncrеаsіngly crіtіcаl tο rеducе thе еnеrgy cοnsumptіοn аnd tο sοlvе thе еnvіrοnmеntаl crіsіs. Thе fοllοwіng cаpstοnе rеpοrt dеscrіbеs а mіxеd-іntеgеr lіnеаr prοgrаmmіng οptіmіzаtіοn аlgοrіthm tο mіnіmіzе thе pеаk dеmаnd аt thе mіcrο grіd lеvеl аnd tο rеducе thе cοst functіοn іn а smаrt hοmе еnvіrοnmеnt. Thе οptіmіzаtіοn mеthοds tаkеs іntο аccοunt thе tіmе vаryіng еlеctrіcіty prіcе аnd thе vаryіng еnеrgy dеmаnd pеаks tο dеtеrmіnе thе mοst suіtаblе tіmе tο usе hοmе аpplіаncеs. Thе аlgοrіthms аrе furthеr usеd tο cοmpаrе thе еnеrgy cοst rеductіοn rеsults wіth аnd wіthοut thе usе οf rеnеwаblе rеsοurcеs аnd mοrе prеcіsеly phοtοvοltаіc mοdulеs. Іn аddіtіοn, thе sіzіng οf а phοtοvοltаіc systеm іs іmplеmеntеd tο аchіеvе furthеr еffіcіеnt еnеrgy οptіmіzаtіοn аnd аpplіаncе schеdulіng. Fіnаlly, а cοst bеnеfіt аnаlysіs іs pеrfοrmеd οn аll thе schеdulіng аlgοrіthms tο dеtеrmіnе whіch іs thе mοst cοst еffеctіvе.

Source: Ashesi
Determining the location of a bus in real-time using LORA technology.

Travelers without prior information about the bus they are waiting, often waste time at bus stations which affects their day activity plan. GPS receivers are used to address this problem by providing real-time about the location of the bus, however, it is quite expensive and power consuming to use and every bus needs to have a GSM/GPRS module to be able to send the information to the internet. This project suggests a low-cost and less power consuming approach of using LoRa technology, geometry methods to determine the location of the bus and only one GSM module for multiple buses to transmit the data to the internet. Results in the project show success in determining the location of the bus in real-time.

Source: Ashesi
Developing a chatbot for e-commerce in Accra: Improving user experience and conversion rates

E-commerce is the process of conducting commerce through computer networks. An individual sitting in front of a computer may use all of the internet's resources to purchase or sell things. Unlike conventional commerce, which is carried out physically with a person's effort to travel and obtain items, e-commerce has made it simpler for humans to eliminate physical labour and save time. This online business management system has also assisted retailers in saving money on upfront costs such as storefronts and staff. This paper presents the design and development of a chatbot to improve e-commerce conversion rates in Accra. Ultimately, the thesis aims to develop a practical and effective tool to help online retailers in Accra improve their businesses and increase their sales through better customer service. The study begins with an overview of the current state of e-commerce in Accra, highlighting the challenges customers face. The study results have shown that chatbots improve user experience on e-commerce websites, reducing their frustrations and making them more likely to make a purchase.

Source: Ashesi
Developing a context-aware automatic playlist generator (CAAPG)

The current digitization of music and the sheer volume of the musical content available to listeners on local devices, such as mobile phones and IPod has been revolutionary. This trend has changed the way humans interact and experience their music. Music listeners can listen to their songs on the move. The most recent trend in the music industry is that users can organize and search for their songs based on emotions. However, most users have to manually create their playlists for particular situations. The work that this entails is cumbersome and sometimes negates the experience of the listener. The intuitive response to this problem is developing an automatic playlist generating (APG) system. Research on APG mostly focuses on using traditional metadata and audio similarity methods to create a playlist. In addition APG is seen as a static problem [1]. This means that APG is seen as a problem that does not change, however music listeners are always changing their listening habits. This thesis supports and follows from the argument made in Chi chung-yi’s work - that the APG problem is a continuous optimization problem. Additionally, in this paper I also argue that the best way to give users a good listening experience is to understand the user’s preference(s) depending on the context. Context here simply mean the features that make up the environmental space in which the system is being used. The main idea in this paper is to show the importance of emotional categorization in the generation of playlist content, while simultaneously mapping those categories to the user’s context based on the users past activities on the system. Reinforcement learning is the method used in this thesis to generate a personalized playlist, based on the context of use and the user’s emotional preference. After implementing the system we use two hypothetical users to simulate the use of our system. Various metrics are defined to measure the performance of this approach.

Source: Ashesi
Developing a Data Visualisation Tool for The Canvas Gradebook

This work encapsulates the stages involved in developing a data visualiser web application, CanSea. It focuses on providing a platform that would aid in an easier way to interpret data. For the development of the proposed system, requirements were gathered to ensure that user needs would be met, and that the system was achieving a purpose. Data visualisation has become an important part of human lives because, from different research papers, it is being used by different fields, including education to cut down time and increase productivity by making data easier to understand. This system was designed to be used by the Ashesi University lecturers and faculty interns, where they can upload csv files exported from Canvas, a learning management system used by the school. The results from this project suggest that the system is feasible and would make it easier to interpret raw data.

Source: Ashesi