Department of Computer Engineering
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Item Maximum Power Point Tracking in Power System Control Using Reservoir Computing(Frontiers in Energy Research, 2022) Seddoh, M.A.; Sowah, R.A.; Sackey, D.M.; et al.This article deals with an innovative approach to maximum power point tracking (MPPT) in power systems using the reservoir computing (RC) technique. Even though extensive studies have been conducted on MPPT to improve solar PV systems efficiency, there is still considerable room for improvement. The methodology consisted in modeling and programming with MATLAB software, the reservoir computing paradigm, which is a form of recurrent neural network. The performances of the RC algorithm was compared to two well-known methods of maximum power point tracking: perturbed and observed (P&O) and artificial neural networks (ANN). Power, voltage, current, and temperature characteristics were assessed, plotted, and compared. It was established that the RC-MPPT provided better performances than P&O-MPPT and ANN-MPPT from the perspective of training and testing MSE, rapid convergence, and accuracy of tracking. These findings suggest the need for rapid implementation of the proposed RC-MPPT algorithm on microcontroller chips for their widespread use and adoption globallyItem Vulnerability Analysis of Online Banking Sites to Cross-Site Scripting and Request Forgery Attacks: A Case Study in East Africa(IEEE 8th International Conference on Adaptive Science and Technology, 2021) Buah, G.; Memusi, S.; Sowah, R.A.; et al.Web applications are prone to several attacks. Two common threats are cross-site scripting attacks and cross site request forgery. With internet banking becoming more popular in East Africa, the level of security that online banking services offer has become an increasing concern. This paper presents an analysis of the safety of these applications used by many unsuspecting customers seeking convenience and determines ways to detect and prevent these attacks from taking place. We assumed that if people with a technical background in IT and information security are vulnerable to CSRF and XSS attacks, the public would be even more vulnerable. Out of 96 users, 35 answered our survey, 53.1% of the respondents said they do not check the URLs of online banking websites they visit to ensure they are not on a phishing site. Secondly, only 36.4% of users considered the security implications of clicking on links in emails or even on banking websites all the time. Based on the interviews done, testing and analysis conducted, there is a clear indication that Internet banking users are vulnerable to XSS and CSRF. Notably, close to 50 % of the Internet banking users we interviewed reported that they do not receive ample tips from the banks regarding security issues to look out for when transacting online. The findings from this research help make recommendations to banks and users to ensure that future online banking transactions are done more securely.Item Think to Speak - A Piezoelectric-EEG system for Augmentative and Alternative Communication (AAC) using Recurrent Neural Networks(EEE Industry Applications Society Annual Meeting, 2019) Sowah, R.; Friedman, R.; Ofoli, A.R.; Sarkodie-Mensah, B.The collection of individuals with severe speech and physical impairments (SSPI), is the target audience for the Think to Speak Augmentative and Alternative Communication (AAC) system. The slow communication rate of AACs accessible to the target audience renders them undesirable, exhausting to operate, and a barrier to social and economic inclusion. This research synergizes the use of Electroencephalography (EEG) and high sensitivity piezoelectric sensor readings with a Long Short-Term Memory Recurrent Neural Network (LSTM RNN) to create a physically accessible AAC with performance comparable to 7.8 characters per minute communication rate. Since self-expression is inextricably linked with physical, mental, and emotional health, this research is of great significance to the estimated one percent of the global population with complex communication needs.Item : Public Wi-Fi Set-Up to Complement Existing Campus Internet Access Provided by the University of Ghana(Newswood Limited, 2023) Aboagye, I.A.; Boadu, E.O.; Wiafe, O-B.; et al.Public Wi-Fi can be found in public places such as airports, coffee shops, University campuses, etc. The ease with which people can access the internet using public Wi-Fi is comparatively the preferred internet access technology and provides comfort to many of its users. The major issues that characterize the public Wi-Fi networks at the University of Ghana especially the School of Engineering Sciences are slow internet speeds, low bandwidth, and weak Wi-Fi signals. Wi-Fi accessibility during peak hours for serious academic work has always been a problem. There is therefore the need to provide improved wireless communication technology with improved internet speeds, higher bandwidths, and stronger signals to complement the Wi-Fi services provided by the University of Ghana. To achieve this, a Wi-Fi network was implemented to provide an alternative to the existing campus Wi-Fi. This was done using fiber optics backhaul, two Altai super Wi-Fi access points (antennas), and a Mikrotik 8 port router. The results showed a significant improvement in performance as compared to the Wi-Fi services provided by the University in terms of strength, signal bandwidth, upload, and download speeds respectively. This will help students and lecturers at the University to conduct their research work smoothly without any disruptions. © 2023 Newswood Limited. All rights reserved.Item Mechanical vibration monitoring system for electrocardiogram machine based on Hilbert-Huang transformations(The Journal of Engineering, 2022) Yongbo, Z.; Lijun, X.; Abubakari, I.S.The monitoring of health and the technologies that are related to it are an exciting area of research. The paper proposes a mechanical manufacturing vibration monitoring system that is based on Hilbert-Huang transformation (HHT) feature extraction to monitor the running state of the spindle of a mechanical numerical control (NC) machine tool of an electrocardiogram (ECG) machine. Real-time monitoring of the time–frequency characteristic quantity of the spindle vibration signal for ECG signals has been made possible due to the online empirical mode decomposition (EMD) method, which is used to obtain the time–frequency characteristic quantity of the spindle vibration signal based on HHT. The experiment shows that the frequency doubling characteristic components in the time– frequency distribution are obvious in the time interval without copper rod contact, but they disappear in the time interval during which copper rods are in contact (0.3 1.1 s, 3 4s in the figure). It has been demonstrated that the system is capable of not only accurately monitoring the characteristic quantity in the frequency domain of the vibration signal produced by the NC machine tool spindle, but also of successfully implementing the monitoring of the time–frequency characteristic quantity in real time.Item Solar Powered Automatic Waste Management System using LoRaWAN(International Conference on Adaptive Science and Technology, 2022) Ansah, M.R.; Akansake, S.N.; Misbawu, A.Solid waste segregation is essential in waste management. This project seeks to present a method of separating four kinds of wastes; metal waste, plastic waste, solid wet waste and paper waste. A short message is sent using LoRaWAN technology to the waste collector alerting him on the status of the waste in the bin. The project has a front ultrasonic sensor which detects the presence of a person 40cm to the bin and then automatically opens the bin for the person to drop the waste. Three sensors made up of inductive and capacitive proximity sensor and a moisture sensor are employed in the dump tray to detect whether the waste is metal, paper or a wet substance and subsequently direct the waste to the appropriate bin. Four other ultrasonic sensors are fitted on top of each of the individual bins to determine the level of the waste in the bins. These four sensors are linked to the front sensor to automatically shut the bin to prevent further addition of waste. A 12volt 60watts solar panel is used to power the system through a lithium rechargeable battery. This project will go a long way to solve the waste challenges wwe have in schools, hotels, hospitals and churchesItem Optimal Location for Loss Reduction on A 7-Bus Bar Power Grid System by Capacitor Placement(International Conference on Adaptive Science and Technology, 2022) Misbawu, A.; Ansah, M.R.; Nchor, S.A.Reduction of power loss in transmission and distribution system is key to improve the efficiency of power system. This paper presents a method of minimizing the loss associated with the reactive component of the branch current by optimal placement of shunt capacitor on an IEEE seven Bus-bar system by Power-World Simulator. The project started by drawing the one-line diagram of the 7-bus power grid system with rated values suggested by the simulator tool. Upon completion, all the data regarding the Voltage per unit, mega volt-ampere reactive losses, megawatt and mega volt ampere at each buss were recorded. Analysis was done on the system using the power world simulator. From the simulation results, the original system recorded a low power factor of 0.79 and a mega volt-ampere reactive loss of eighteen percent (18%). After analyzing the system and installing the capacitor bank at the optimal location, the power factor improved to 0.98 and the system’s mega volt ampere reactive reduced to 6.4%. The optimal location for the capacitor bank was identified as the bus that injects more reactive power to the system. The bus also has a low voltage per unit value and high conductance as compared to all other buses.Item Risk assessment framework for cumulative effects (RAFCE)(Frontiers in Environmental Science, 2023) Antwi, E.K.; Boakye-Danquah, J.; Owusu-Banahene, W.Introduction: Regional environmental risk assessment is a practical approach to understanding and proactively addressing the cumulative effects of resource development in areas of regional importance. However, regional assessment is methodologically complex, and frameworks to identify and prioritize regional risk issues to guide effective management decisions are lacking. This research develops a risk and impacts-based cumulative effects assessment framework for scoping regional cumulative effects issues to guide present and future project and regional assessment. We operationalized the framework dubbed Risk Assessment Framework for Cumulative Effects (RAFCE) to assess the risks and impacts of proposed mining development in the Ring of Fire region of Northern Ontario, Canada. Methods: Methodologically, we built on existing studies to understand the key valued ecosystem components (VECs) impacted by mining; organized an expert Bowtie Risk Assessment Tool workshop and interviews to identify regional risks and define the VECs impacted by mining; and developed an impact prioritization model that helped quantify and prioritize impacts of mining. Results and Discussion: RAFCE enabled us to: a) identify drivers and impacts of cumulative effects and potential preventive and mitigation measures for effective cumulative effects management and b) describe, quantify, and rank the major impact and components of regional interest. Using RAFCE, we can identify and prioritize impacts that are cross-cutting, multisector-driven, synergistic, and relevant to a region, visualize and understand the risk management process, identify policy and management issues to prevent risks or mitigate impacts, and ultimately inform resource allocation for effective regional cumulative effects assessment outcomes. RAFCE is suitable for engaging diverse stakeholders in planning for regional cumulative effects assessment.Item Improved Multisignature Scheme for Authenticity of Digital Document in Digital Forensics Using Edward-Curve Digital Signature Algorithm(Security and Communication Networks, 2023) Shankar, G.; Ai-Farhani, L.H.; Samori, I.A.At the moment, digital documents are just as important as paper documents. As a result, authenticity is essential, especially in legal situations and digital forensics. As technology advances, these digital signature algorithms become weaker, necessitating the development of digital authentication schemes capable of withstanding current security threats. Tis study proposed a scheme based on an asymmetric key cryptosystem and the user’s biometric credentials to generate keys for digital signatures. A single document can be signed by multiple signatories at the same time under this scheme. Te primary goal of this article is to create a safe and cost-effective multigeniture scheme. To create keys for document signing and verification, the Edwards-curve Digital Signature Algorithm (EdDSA), especially Ed25519, is employed. Te Edwards-curve Digital Signature Algorithm is used with blockchain technology to sign crypto wallets. Te Python implementation of a scheme that enables platform independence. We performed performance, security, and comparative analysis to ensure maximum usability. The article’s main finding's are that the Ed25519 algorithm can be used in blockchain.Item Optimal sizing and techno-economic analysis of a hybrid solar PV/wind/diesel generator system(IOP Conference Series: Earth and Environmental Science, 2022) Tay, G.; Acakpovi, A.; Adjei, P.; Aggrey, G.K.; Sowah, R.; et al.Abstract. Hybrid power systems that combine wind and solar PV technology have been widely employed for power generation, particularly for electrification in remote and islanding locations, because they are more cost-effective and reliable than traditional power systems. This article intends to develop an environmentally friendly and cost-effective hybrid power system for selected critical loads in the Avuto community of Ghana. Following the acquisition of site data, a hybrid solar PV, wind, diesel generator, and converter analysis was conducted using HOMER software to establish the appropriate sizing of system components based on technical and economic parameters such as load served, annual electricity production, net present cost (NPC), emission, Operating cost, Fuel consumption and energy cost (COE). Based on the optimization computational results, it can be stated that the combination of system components, including solar photovoltaic, wind turbine, and diesel generator, is a good fit for the application region and might be used for rural and island electrification in the future. The suggested energy system has an LCOE of 0.39 US$/kWh for the 1.08 US$/litre diesel fuel cost and a 3.33-year payback period, with 58.8 kW for PV, 7 units for 3 kW wind turbines, 10 kW for diesel generator, and 6.99 kW for the converter. In terms of emission reduction, the proposed case presented a 55% emission reduction from the base case scenario.Item Innovative design of grid connected solar/diesel hybrid system using RETScreen software(IOP Conference Series: Earth and Environmental Science, 2022) Kof, D.; Acakpovi, A.; Adjei, P.; Sowah, R.; Aggrey, G.K.; et al.Abstract. Accessibility to dependable energy resource is vital to the emerging economy to function appropriately in this contemporary world for both residential and commercial purposes. Technological advancement has opened avenues for more sophisticated technologies to combine multiple energy sources to generate affordable electricity for residential and industrial purposes. The study, therefore aims at analyzing the fiscal benefits of hybrid Solar PV and Diesel Generator (DG) (PV-DG) grid-connected system using RETSceen software. The study focused on a specific location, J. A. Plant Pool Ghana Limited, warehouse Department. The study recommended and proposed an effective design of a hybrid PV-DG grid connected electricity supply for the warehouse Department. The economic viability of the project and the payback period obtained through computation were very attractive. Also, the total revenue of electricity exported to the grid annually and GHG emission reduction were within the standard benchmark. The study finally concurred that renewable energy sources such as solar when hybridized with any other energy systems, lead to a noticeable electrical cost reduction. Therefore, this system design provides multiple benefits, including; improved reliability, reduced emission and significant cost reduction.Item An automated method for developing search strategies for systematic review using Natural Language Processing (NLP)(MethodsX, 2023) Kwabena, A.E.; Wiafe, O-B.; John, B-D.; Bernard, A.; Boateng, F.A.F.The design and implementation of systematic reviews and meta-analyses are often hampered by high financial costs, significant time commitment, and biases due to researchers’ familiarity with studies. We proposed and implemented a fast and standardized method for search term selection using Natural Language Processing (NLP) and co-occurrence networks to identify relevant search terms to reduce biases in conducting systematic reviews and meta-analyses. • The method was implemented using Python packaged dubbed Ananse, which is benchmarked on the search terms strategy for naïve search proposed by Grames et al. (2019) written in “R”. Ananse was applied to a case example towards finding search terms to implement a systematic literature review on cumulative effect studies on forest ecosystems. • The software automatically corrected and classified 100% of the duplicate articles identified by manual deduplication. Ananse was applied to the cumulative effects assessment case study, but it can serve as a general-purpose, open-source software system that can support extensive systematic reviews within a relatively short period with reduced biases. • Besides generating keywords, Ananse can act as middleware or a data converter for integrating multiple datasets into a database.Item Development of a Mobile Application Platform for Self Management of Obesity Using Artificial Intelligence Techniques(Hindawi, 2021) Sefa-Yeboah, S.M.; Annor, K.O.; Koomson, V.J.; Saalia, F.K.; Steiner-Asiedu, M.; Mills, G.A.Obesity is a major global health challenge and a risk factor for the leading causes of death, including heart disease, stroke, diabetes, and several types of cancer. Attempts to manage and regulate obesity have led to the implementation of various dietary regulatory initiatives to provide information on the calorie contents of meals. Although knowledge of the calorie content is useful for meal planning, it is not sufficient as other factors, including health status (diabetes, hypertension, etc.) and level of physical activity, are essential in the decision process for obesity management. In this work, we present an artificial intelligence- (AI-) based application that is driven by a genetic algorithm (GA) as a potential tool for tracking a user’s energy balance and predicting possible calorie intake required to meet daily calorie needs for obesity management. The algorithm takes the users’ input information on desired foods which are selected from a database and extracted records of users on cholesterol level, diabetes status, and level of physical activity, to predict possible meals required to meet the users need. The micro- and macronutrients of food content are used for the computation and prediction of the potential foods required to meet the daily calorie needs. The functionality and performance of the model were tested using a sample of 30 volunteers from the University of Ghana. Results revealed that the model was able to predict both glycemic and non-glycemic foods based on the condition of the user as well as the macro- and micronutrients requirements. Moreover, the system is able to adequately track the progress of the user’s weight loss over time, daily nutritional needs, daily calorie intake, and predictions of meals that must be taken to avoid compromising their health. The proposed system can serve as a useful resource for individuals, dieticians, and other health management personnel for managing obesity, patients, and for training students in fields of dietetics and consumer science.Item Hardware Module Design and Software Implementation of Multisensor Fire Detection and Notification System Using Fuzzy Logic and Convolutional Neural Networks (CNNs)(Hindawi Journal of Engineering, 2020-02-01) Sowah, R.A.; Apeadu, K.; Gatsi, F.; Ampadu, K.O.; Mensah, B.S.)is paper presents the design and development of a fuzzy logic-based multisensor fire detection and a web-based notification system with trained convolutional neural networks for both proximity and wide-area fire detection. Until recently, most consumer-grade fire detection systems relied solely on smoke detectors. )ese offer limited protection due to the type of fire present and the detection technology at use. To solve this problem, we present a multisensor data fusion with convolutional neural network (CNN) fire detection and notification technology. Convolutional Neural Networks are mainstream methods of deep learning due to their ability to perform feature extraction and classification in the same architecture. )e system is designed to enable early detection of fire in residential, commercial, and industrial environments by using multiple fire signatures such as flames, smoke, and heat. )e incorporation of the convolutional neural networks enables broader coverage of the area of interest, using visuals from surveillance cameras. With access granted to the web-based system, the fire and rescue crew gets notified in real-time with location information. )e efficiency of the fire detection and notification system employed by standard fire detectors and the multisensor remote-based notification approach adopted in this paper showed significant improvements with timely fire detection, alerting, and response time for firefighting. )e final experimental and performance evaluation results showed that the accuracy rate of CNN was 94% and that of the fuzzy logic unit is 90%.Item Decision Support System (DSS) for Fraud Detection in Health Insurance Claims Using Genetic Support Vector Machines (GSVMs)(Journal of Engineering, 2019-09-02) Sowah, R.A.; Kuuboore, M.; Ofoli, A.; Kwofie, S.; Asiedu, L.; Koumadi, K.M.; Apeadu, K.O.Fraud in health insurance claims has become a significant problem whose rampant growth has deeply affected the global delivery of health services. In addition to financial losses incurred, patients who genuinely need medical care suffer because service providers are not paid on time as a result of delays in the manual vetting of their claims and are therefore unwilling to continue offering their services. Health insurance claims fraud is committed through service providers, insurance subscribers, and insurance companies. (e need for the development of a decision support system (DSS) for accurate, automated claim processing to offset the attendant challenges faced by the National Health Insurance Scheme cannot be overstated. (is paper utilized the National Health Insurance Scheme claims dataset obtained from hospitals in Ghana for detecting health insurance fraud and other anomalies. Genetic support vector machines (GSVMs), a novel hybridized data mining and statistical machine learning tool, which provide a set of sophisticated algorithms for the automatic detection of fraudulent claims in these health insurance databases are used.(eexperimental results have proven that the GSVM possessed better detection and classification performance when applied using SVM kernel classifiers. (ree GSVM classifiers were evaluated and their results compared. Experimental results show a significant reduction in computational time on claims processing while increasing classification accuracy via the various SVM classifiers (linear (80.67%), polynomial (81.22%), and radial basis function (RBF) kernel (87.91%).Item Impact Analysis of Induced FM Radio Interferences on Aeronautical Radio Navigation Systems: Case Study of Kotoka International Airport, Accra-Ghana(International Conference on Computing, Computational Modelling and Applications, 2019-03-29) Sowah, R.; Acakpovi, A.; Tefutor, I.; Quist-Aphetsi, K.; Nwulu, N.; Abubakar, R.This paper investigates the effect of interference on Aeronautical Navigation systems by Frequency Modulation (FM) broadcasting signals. Precisely, the paper evaluated the impact of 3rd order intermodulation distortion on the VHF omnidirectional range and the instrument landing system (Localizer) used at the Ghana Civil Aviation Authority (GCAA). The necessity of this study stems from the fact that, electromagnetic compatibility (EMC) between FM audio broadcast and aeronautical radio communication services operating in the range of 85.7-108MHz and 108-117.975 MHz respectively is essential for safe flight operation. An analytical method of estimating the 3rd order intermodulation distortion has first been presented followed by simulation approach with the intermodulation analysis software v.10 and subsequent simulation with the Matlab software to determine and display the power spectral density of the output signals. All FM station frequencies in the Greater Accra region have been considered and paired to form dual tone signals that were considered input signal before assessing the impact of the 3rd order intermodulation harmonic. It was found that multiple 3rd order intermodulation harmonics distort and perturbate the aeronautical communication system in the Greater Accra region and these lead to severe safety implications for the operation of the aeronautical navigation system. It was recommended that broadcasting stations should implement cavity filters to reduce the effect of 3rd order intermodulation harmonics; they should respect the specification prescribed to them by the NCA and operate within limits allocated to them in order not to breach the international regulation of ITU that deems it an offense to interfere with the aeronautical communication system and to further ensure safety to the aviation navigation system.Item Modelling an Efficient Gap Filler for DTT Network Using ADS Software(International Conference on Computing, Computational Modelling and Applications, 2019-03-29) Sowah, R.; Mensah, F.; Acakpovi, A.; Osumanu, F.; Fifatin, F.N.; Nounangnonhou, T.C.This paper proposes the modelling and simulation of a special gap filler intended to cover grey areas in the DTT network of Accra. This has become necessary due to the numerous areas of low signal coverage in the Accra DTT and the incapability of previous methods to efficiently address the problem. The ADS simulation consists of arrangements of components from the DBV-T library which consists of filters, amplifiers and a power source. This setup mimics a gap filler system with a better noise reduction implementation, several frequency values are being used for the simulation process. A significant increase in the output signal as in comparison to the input means the shaded areas will be properly covered. The results derived from the simulation of the ADS setup highly improved upon the output signal values, when compared to the ITU standard. Three (3) out of five (5) simulation results show values beyond the minimum signal level requirement. Also using MATLAB, the RF propagation toolbox which has the map tool feature was able to implement the gap fillers into the Accra area and gave a visual representation of the signal strength. Modelling a gap filler system which has better noise cancellation and which propagates better with a dipole antenna was achieved in this paper. The outcome of the paper shows that the gap filler modelling increase signals in grey areas.Item Rotational Energy Harvesting To Prolong Flight Duration of Quadcopters(IEEE Transactions on Industry Applications, 2017-10) Sowah, R.A.; Acquah, M.A.; Ofoli, A.R.; Mills, G.A.; Koumadi, K.M.This paper presents a rotational energy harvester using a brushless dc (BLdc) generator to harvest ambient energy for quadcopter in order to prolong it flight duration. For a quadcopter, its endurance is essential in order to achieve operational goals such as scientific research, security, surveillance, and reconnaissance. Because quadcopters have a limitation on size and mass, they cannot carry a large mass of on-board energy thereby having short flight time. In this paper, BLdc generators are coupled with the propellers of the quadcopter to transfer kinetic energy from the propellers to the generator. Taking into consideration the power requirement of quadcopter, the output of the generator is amplified using dc-dc boost, and is regulated to power and charge the on-board battery. The BLdc generator is simulated in MATLAB/Simulink. A final prototype of the rotational energy harvesting system is built, and this comprises a quadcopter, power management system, and a battery charging system. © 1972-2012 IEEE.Item Detection and Prevention of Man-in-the-Middle Spoofing Attacks in MANETs Using Predictive Techniques in Artificial Neural Networks (ANN)(Journal of Computer Networks and Communications, 2019-01) Sowah, R.A.; Ofori-Amanfo, K.B.; Mills, G.A.; Koumadi, K.M.A Mobile Ad-Hoc Network (MANET) is a convenient wireless infrastructure which presents many advantages in network settings. With Mobile Ad-Hoc Network, there are many challenges. These networks are more susceptible to attacks such as black hole and man-in-the-middle (MITM) than their corresponding wired networks. This is due to the decentralized nature of their overall architecture. In this paper, ANN classification methods in intrusion detection for MANETs were developed and used with NS2 simulation platform for attack detection, identification, blacklisting, and node reconfiguration for control of nodes attacked. The ANN classification algorithm for intrusion detection was evaluated using several metrics. The performance of the ANN as a predictive technique for attack detection, isolation, and reconfiguration was measured on a dataset with network-varied traffic conditions and mobility patterns for multiple attacks. With a final detection rate of 88.235%, this work not only offered a productive and less expensive way to perform MITM attacks on simulation platforms but also identified time as a crucial factor in determining such attacks as well as isolating nodes and reconfiguring the network under attack. This work is intended to be an opening for future malicious software time signature creation, identification, isolation, and reconfiguration to supplement existing Intrusion Detection Systems (IDSs).Item A Fire-Detection and Control System in Automobiles: Implementing a Design That Uses Fuzzy Logic to Anticipate and Respond(IEEE Industry Applications Magazine, 2019-01) Sowah, R.; Ampadu, K.O.; Ofoli, A.R.; Koumadi, K.; Mills, G.A.; Nortey, J.Despite the immense benefits of fire detection in road transport, more than 2,000 vehicles are damaged by unexpected fires on a daily basis. On a global scale, incendiary-based losses for the automobile and insurance industries have run in to the billions of dollars in the past decade. One contributing factor is the lack of a sophisticated fire safety system in automobiles. This has been addressed by designing and implementing fuzzy logic control systems with feedback over an Arduino microcontroller system. The automatic system, consisting of flame, temperature, and smoke sensors as well as a re-engineered mobile carbon dioxide (CO 2 ) air-conditioning unit, was tested on a medium-sized physical car. Results suggest that the automobile fire-detection and control system, devoid of false alarms, detects and extinguishes fire in under 20s. An innovative, very promising modular solution for hardware implementation in fire detection and control for automobiles has been developed by using new algorithms and fuzzy logic.