ghanaopendata/ghanaian-research-english huggingface dataset:
Seamless payments with mode-of-payment abstraction

In the last few decades, considerable progress has been made around payment interoperability and the world's continued push toward increasing e-commerce volumes has necessitated innovation in the digital payments space. Today, users have to deal with a scattered payment landscape where multiple payment processors exist and users have to grapple with how they send and receive money across the varying payments processors. "Mode-of-Payment Abstraction" represents a different way of processing transactions that effectively enables users to complete transactions without the need to know what specific e-wallet type a recipient of a transaction is using and vice versa. It hides this level of detail from the paying and receiving ends of a transaction, allowing individuals to only think at the level of "who" without any regards for the "how". Mode-of-payment abstraction seeks to make the notion of different payment modes and processors obsolete to individuals and businesses, enabling true payment interoperability across all payment types. This capstone project explores the framework that must exist to support a mode-of-payment abstraction based system and implements such a service.

Source: Ashesi
Securing power grids with power system asset monitoring of transformers

This project is a transformer health monitoring system, which is a breakthrough solution developed to improve grid reliability and security by continuously assessing the state of transformers and associated equipment. The system measures real-time key operational parameters such as temperature, humidity, gas and vibration using various sensors. An ESP32 microcontroller handles the data, and communication is carried out using a SIM800L GSM module to alert information via SMS. The other part will be uploaded to a cloud-based platform for further analytical studies. The system comprises an LCD screen that can be installed on-site and a buzzer for real-time alerts in critical conditions. The device can also detect mechanical stresses by placing an MPU6050 accelerometer and a gyroscope, showing early warning signs of future failures. After collecting all the data, this system will predict transformer failures before they occur and allow owners to prevent them, decreasing downtime and maintenance costs. This study demonstrates how modern monitoring methods may be applied to improve power grid applications' security and efficiency.

Source: Ashesi
Semi-autonomous agricultural crop sprayer for medium-scale farms in Ghana

Most small-scale farmers in Ghana that have transitioned into medium-scale farming are currently using lever-operated Knapsacks for fertilizer/pesticide application. For farm sizes above five hectares, it becomes inefficient and labour intensive, resulting in health issues. Efficient methods like drones and tractors are expensive. Hence, the need to design and fabricate a cost-effective, semi-autonomous sprayer with low labour intensity. This project designs and fabricates a mechanical system equipped with a nozzle and navigation control system. The nozzle system turns the nozzles on and off and directs the crop sprayer via Bluetooth. The nozzle control system also has flow sensors that measure the flow rate from each nozzle. Results obtained from testing the system show that the on and off control of one nozzle increases the flow rate in the other nozzle, which can be attributed to an increase in pressure. Also, the cost of automating the system is cost-effective for medium-scale farmers. The system was able to control the nozzles for potential savings for farmers while reducing manual labour.

Source: Ashesi
SEMPLE (Self Employment Makes People Lives Easier) A platform to promote self-employment of people while providing avenues for people to get full-time employment in Ghana

The evolution of technology over the years has opened many opportunities in many fields of life. The sectors of our economy, such as health, agriculture, entertainment, have all been improved. This evolution gives a new opportunity to people in marketing themselves. Africa could be said to be behind with some of these technologies, but it is making progress. A sector Africa requires some more technological advancement is the employment and job sector. From the hiring process to the management, to the working styles, to name a few. Ghana, though rich in skilled human resource, still seem to have a relatively high unemployment rate. Reasons including, lack of knowledge on creating a resume, difficulty in the job search process offline and online (for cases where openings are not centralized). This research study seeks to propose the encouragement of self-employment through a web platform, whose features are mainly: • To aid people to get contract jobs • To help with outsourcing jobs • To allow users to leverage their skills online • To enable the creation of portfolios and resumes with ease • To provide a job board for users looking to secure full-time positions • To allow Employers to have a more streamline process when employing

Source: Ashesi
SensePay: Embedded IMU Intelligemce and Machine Learning for Relay Attack Prevention in Contactless Payments.

As contactless payment systems continue to expand, they remain exposed to relay attacks that exploit the absence of physical proximity verification. This research proposes SensePay, a lightweight, orientation-based fraud detection framework that enhances NFC payment security by embedding motion sensing and machine learning into the transaction process. A 6-axis IMU captures real-time device orientation (pitch, roll) and transaction timing, which are analyzed by a trained One-Class SVM model running locally on an ESP32 microcontroller. Experimental evaluation demonstrated that the system achieves 96.7% classification accuracy and maintains sub-300 ms transaction latency, outperforming traditional statistical threshold methods. Both delay-based and orientation-based relay attacks were successfully detected, confirming the approachscy, or user convenience, paving the way for stronger and scalable contactless payment security.

Source: Ashesi
Sensepay: Embedded Imu Intelligence And Machine Learning For Relay Attack Prevention In Contactless Payments

Climate finance is essential for Ghanaes the political factors (leadership commitment, policy consistency, and donor conditionalities) that influence funding flows; the mechanisms by which climate finance is allocated (budgetary support, sectoral allocations, project-based funding, and public-private partnerships, ); and the challenges (limited technical capacity to competing national priorities, low public awareness). Findings highlight that robust governance structures, clear institutional frameworks, and effective coordination are vital for improving mobilization and allocation. The study recommends strengthening domestic resource mobilization, establishing a dedicated climate action fund, enhancing local technical capacity, incentivizing private sector engagement, and reinforcing transparency and accountability mechanisms. Addressing Ghanaesn need.

Source: Ashesi
Sickle cell pain clinic and the work productivity of the Ghanaian adult with sickle cell disease

Sickle Cell Disease (SCD) is highly prevalent in Ghana, as the origins of the disease stem from the West African Region and countries along the equator with an incidence of malaria. The disease presents sufferers with a life of chronic pain and thus affects the quality of life and work productivity of individuals with SCD. Sickle Cell Pain clinics are specialised centres that provide a multidisciplinary approach to pain management by using non-pharmacological treatments, physical therapy, and psychological support. This study aims to examine the effects of Sickle Cell Disease on the work productivity of Ghanaian working adults and to assess whether their access to Sickle Cell pain clinics would contribute to an improvement in their work productivity. Seven (7) SCD patients from the Accra, Tema and Kumasi, consisting of both male and female adults between the ages of 18 and 50 years, were recruited to participate in the study using convenience sampling and underwent semi-structured interviews to share their lived-in experiences with SCD and how SCD has impacted their professional lives, the effect of SCD on their work productivity, their understanding of SCD pain Clinics and finally, their perception of what benefit SCD pain clinics would have on their work productivity, if they existed in Ghana. The results showed that SCD had influenced the type of work the participants engage in, and all participants had also experienced a reduced level of work productivity due to consistent complications caused by SCD. The insights gained were that SCD, with its associated chronic pain and crises, took a toll on all participants' mental health. All participants perceived that Sickle Cell Pain clinics would be an invaluable resource to them, offering counselling support and relaxation therapies, and possibly reducing their hospital visits by half.

Source: Ashesi
signWithMe: Intelligent Learning System for Inclusive Learning of the Ghanaian Sign Language

Though Machine Learning has been around for a while, it is still considered a new tool for economists and in its application to predicting economic growth. Studies that apply machine learning to predicting economic growth have found that the Random Forest algorithm is currently the best performing machine learning algorithm for predicting economic recessions and economic growth. However, besides studies evaluating the various machine learning algorithms, there is limited literature on the application of these techniques to help economists and policymakers solve problems. Developing African countries, like Zimbabwe, with their unique economic growth challenges, can harness the predictive qualities of this technology in development planning, setting, and achieving growth targets. In this thesis, I apply the random forest algorithm to make income predictions for Zimbabwe, in the country's hopes to attain upper-middle-income status by 2030.

Source: Ashesi
signWithMe: Intelligent learning system for inclusive learning of the Ghanaian Sign Language

There are many Deaf people in the world, and in Ghana, there are many Deaf persons. However, there is a huge communication gap between the Deaf and hearing in the Ghanaian society, as there is inadequate teaching and learning of the Ghanaian Sign Language. In this project, the signWithMe application system seeks to address this problem by providing a Sign Language application system that consists of a Sign Language dictionary, a translator, an eresource, an e-forum and an e-payment system. It would educate people about the Deaf community to ensure diversity and inclusion in our society. This system will use web features, a payment and a chatbot Application Programming Interface (API).

Source: Ashesi
Simulated avatar-based environment with chat and resource sharing capabilities

In our world today, we see the evolution of the communication paradigms all with the aim of ensuring a quick and quality way of passing information from one subject to another in different locations. Currently, with the advent of the internet, many efforts are being made to make communication socially immersive; in a way that the person you are communicating with feels naturally close to you. With the inclusion of visual data like pictures, emoticons and videos, people are able to relive past events they missed and are able to have a more realistic sense of how that party, dance, wedding or funeral went. More over the addition of these extra data apart from the traditional text and voice, are able to convey the unspoken words; the emotions, after all a picture can say a 1000 words. This report presents a revolutionary communication product that is supposed to take communication to a whole new level; creating the opportunity for people to accomplish some task otherwise unimaginable on the traditional communication systems.

Source: Ashesi
Simulation of a robotic prosthesis: Using reinforcement learning

Robotic prosthesis is becoming more and more popular today. Robots trained to interact with objects can be used in different fields as it opens the possibility of having robots that interact more smoothly with the environment. In recent years, there have been numerous breakthroughs in using reinforcement learning to program robots. This has resulted in robots being able to solve tasks dynamically and reasonably. Aiming at making robot agents eventually act sensibly when interacting with the objects, we explore two different kinds of programming techniques, using reinforcement learning, and by programming the robot to work based on sensor input. The experiment results demonstrate that the agent acting based on sensor input performed best with limited resources, making a robotic arm operating using sensors a conceivable prosthesis.

Source: Ashesi
Skaïgreen: An aerial drone and deep learning project for the counting and nitrogen deficiency detection of coconut trees

This capstone project involved the implementation of a drone system to obtain an aerial view of a coconut farm, with the goal of using deep learning models to detect and count coconut plants, as well as identify nitrogen-deficient plants. The YOLOv5 algorithm was used for object detection, with a unique ID assigned to each plant for counting. A VGGNet convolutional neural network was trained on a dataset of labeled coconut plant images to classify plants as "healthy" or "unhealthy". The results of the project included an automated drone system that could fly and capture footage with a single click, allowing for efficient counting of coconut plants and detection of nitrogen-deficient plants.

Source: Ashesi
Smart bus system

This project aimed to develop a Smart Bus System (SBS) for tracking the real-time location of a bus using a TTGO T-Beam ESP32 LoRa 433MHz for GPS-coordinated transmission. This system enables the users to track and monitor the bus's location and expected arrival time at their location. Users are required to authenticate themselves and book a bus before tracking it. The system also uses an RFID reader for cashless payment. The user scans their ID card when the bus arrives at their location, and the information is used to update the number of people currently onboard the bus. The date is then stored in a database and accessed from a Django web application. The web application uses Google Maps API to display the bus's location and estimated arrival time. The system design includes two devices: a transmitter placed on the bus and a receiver connected to a wifi source. The transmitter transmits GPS-coordinated data to the receiver, which pushes the data to the database in real time. The Django web application then read the bus coordinates from the database. With the help of Google Maps API, it displays the current location of the bus and the estimated arrival time. The system's development used technology, including ESP32, LoRa, Google Maps API, Django, and RFID reader. The software development process involved writing code for data transmission, reception, and validation modules and creating the Django web application for showing the bus' location and accepting cashless payments. Testing involved testing the system's real-time data transmission, reception, validation, and functional web application testing. The system was tested to function correctly and meet the project's requirements.

Source: Ashesi
Smart home design for the elderly and disabled

The elderly and disabled in society are largely ignored in the design of traditional homes. This paper explores how smart homes can assist the elderly and disabled in living independently by designing a system which makes use of two interfaces: gesture and voice control to allow the elderly and disabled to interact with new smart home technologies such as device control and energy monitoring. The categories of disabled people the project aims to address are paralyzed people, blind people and mute people. The scope of work is limited to designing and implementing a smart home that addresses energy saving through power monitoring and control while providing manual control using an override. In the end, the paper shows that the design can successfully implement the two interfaces with smart home technology by using a Raspberry Pi, ESP32 microcontrollers and the MQTT Protocol to achieve home automation and energy monitoring.

Source: Ashesi
Smart home energy management system using Internet of Things

Global energy demand is increasing rapidly, and carbon dioxide emissions and global warming have become a worldwide central issue, prompting many countries to switch to renewable energy sources. However, the integration of variable renewable energy sources into the power grid, on the other hand, is posing technical issues to the traditional grids. Since residential and commercial buildings account for 40% of the national energy consumption and are still increasing due to population growth, the monitoring information for the deployed grids that serve them is only available on the operator side. Thus, there is a need to counteract the existing grid architecture by having a system that integrates renewable energy sources and has demand-side customer-driven management. There has been tremendous growth in the energy sector in recent years, where smart grid technology was invented and continuously improved. Through this project, a prototype of a smart home energy management system using the Internet of Things that integrates renewable energy sources and is customer-driven is designed and built. The system monitors the environmental conditions in the rooms like temperature and light intensity and the occupancy and controls the electrical appliances, respectively. It also shifts the loads to an energy storage battery during peak hours.

Source: Ashesi
Smart Pen for Real-Time Handwriting Recognition

Modern handwriting recognition systems often require unnatural setups, such as writing on special digital surfaces or wearing motion-tracking gloves, which limits their practicality. This capstone project addresses these limitations by developing a portable smart pen attachment for real-time handwriting recognition on any surface. The device incorporates an inertial measurement unit (IMU) and a low-power microcontroller to capture pen motion and run a machine learning algo- rithm directly on board. Unlike prior digital pens, the electronics module is detachable and can be clipped onto standard pens, allowing users to freely switch writing instruments. A companion mobile application connects via Bluetooth Low Energy to display transcribed text instantaneously, providing immediate visual feedback without the need for special writing surfaces. Evaluation of the system demonstrates high accuracy and robust performance across diverse conditions. The best machine learning model (a bidirectional LSTM network) achieved approximately 90% character recognition accuracy, maintaining around 85

Source: Ashesi
Smart portable low-cost water quality checker

Water quality checking is an essentiality in the manufacture of drinking water which is required and done in all water manufacturing and distribution companies. However, it is required that the quality of water be checked at the distribution end as well, as the quality is reduced due to plumbing contamination, leakages, and prolonged storage to mention a few. The checking of water quality in the urban home is not common in Ghana and those who check through water quality specialists get the results after a number of days during which the sample could be exposed to more contamination. The work done in this project employs different technologies in building a low-cost sensor device which is easy to use by the lay man through a web application.

Source: Ashesi
Smart stethoscope

Accurate auscultation is an essential component of medical diagnosis, but in resource limited settings like Africa, the shortage of physicians often limits access to this crucial part of medical diagnosis. This paper proposes a low-cost smart stethoscope that records sound on an SD card, sends it via the internet to a client computer with a Graphical User Interface (GUI), and provides features for diagnosis, such as a phonograph (auscultated audio wave), heart rate calculation, and splitting of heart and lung sounds. These features extracted from the audio file can be useful for medical diagnosis of heart and lung related conditions. The results demonstrate that the smart stethoscope is a potential to be a better alternative to traditional stethoscopes, with great filtering abilities and the ability for remote diagnosis and treatment of patients. The device s remote capabilities make it particularly valuable in resource-limited settings where access to quality healthcare is a challenge.

Source: Ashesi
Smart systems and the Internet of Things (IoT) for waste management

Waste management is a raising concern faced by many nations in the world today. On the streets of major cities, it has become almost common to find waste which poses health hazards and other concerns to its communities and inhabitants. This project focuses on the use of smart systems and the Internet of Things (IOT), to provide an efficient and effective approach to waste management. This project designed and manufactured a prototype of a solar powered, self-compacting smart bin with a server side monitoring application. The prototype smart bin is capable of monitoring internal rubbish levels, compact it, freeing approximately 25% of the space with each compaction space. The bin also monitors total weight and is capable of sending all these information to a secure server side application. The accompanying web application monitors the state of each smart bin and proposes optimal routes for pick up. This approach will contribute to a smart and efficient waste disposal improving the cites waste management.

Source: Ashesi
Smart vehicle detection traffic management system enhanced with IoT and machine learning

Traffic congestion is amjor thief of time of the citizens of Ghana especially in urban areas like Accra. Due to the high demand of transportation services in urban areas, which is continually increasing day in day out, the problem has become prevalent in the Ghanaian society. The problem of traffic congestion affects the productivity of the working population negatively because of the time lost in traffic jams. Automated traffic lights and traffic instructors are doing their best to try and combat the traffic congestion however these measure are not dynamic enough to solve the problem. Consequently, this problem serves as a motivation to find a better way to handle traffic congestion in urban areas; hence, this paper delves into the use of the internet of things approach coupled with computer vision and machine learning techniques to develop a smart traffic management system based on a vehicle detection algorithm.

Source: Ashesi