UWCScholar :: Browsing by Author "Bagula, Antoine"

Browsing by Author "Bagula, Antoine"

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A calibration report for wireless sensor-based weatherboards
(MDPI, 2015) Muthoni, M.; Bagula, Antoine
Sub-Saharan Africa contains the highest number of people affected by droughts. Although this can easily be mitigated through the provision of timely, reliable and relevant weather forecasts, the sparse network of weather stations in most of these countries makes this difficult. Rapid development in wireless sensor networks has resulted in weatherboards capable of capturing weather parameters at the micro-level. Although these weatherboards offer a viable solution to Africa's drought, the acceptability of such data by meteorologists is only possible if these sensors are calibrated and their field readiness scientifically evaluated. This is the contribution of this paper; we present results of a calibration exercise that was carried out to: (1) measure and correct lag, random and systematic errors; (2) determine if Perspex was an ideal material for building sensor boards' enclosures; and (3) identify sensor boards' battery charging and depletion rates. The result is a calibration report detailing actual error and uncertainty values for atmospheric pressure, humidity and temperature sensors, as well as the recharge and discharge curves of the batteries. The results further ruled out the use of Perspex for enclosing the sensor boards. These experiments pave the way for the design and implementation of a sensor-based weather monitoring system (SenseWeather) that was piloted in two regions in Kenya.
Clustered data muling in the internet of things in motion
(MDPI, 2019) Tuyishimire, Emmanuel; Bagula, Antoine; Ismail, Adiel
This paper considers a case where an Unmanned Aerial Vehicle (UAV) is used to monitor an area of interest. The UAV is assisted by a Sensor Network (SN), which is deployed in the area such as a smart city or smart village. The area being monitored has a reasonable size and hence may contain many sensors for efficient and accurate data collection. In this case, it would be expensive for one UAV to visit all the sensors; hence the need to partition the ground network into an optimum number of clusters with the objective of having the UAV visit only cluster heads (fewer sensors). In such a setting, the sensor readings (sensor data) would be sent to cluster heads where they are collected by the UAV upon its arrival. This paper proposes a clustering scheme that optimizes not only the sensor network energy usage, but also the energy used by the UAV to cover the area of interest. The computation of the number of optimal clusters in a dense and uniformly-distributed sensor network is proposed to complement the k-means clustering algorithm when used as a network engineering technique in hybrid UAV/terrestrial networks. Furthermore, for general networks, an efficient clustering model that caters for both orphan nodes and multi-layer optimization is proposed and analyzed through simulations using the city of Cape Town in South Africa as a smart city hybrid network engineering use-case.
Clustered Multi-layer Multi-protocol Wireless Mesh Networks
(Telkom, 2015) Abdalla, Taha; Rey-Moreno, Carlos; Tucker, William David; Bagula, Antoine
Wireless Mesh Networks (WMNs) have emerged as an alternative option to the wired networks in areas where wired deployment is unfeasible and/or costly. They have been widely adopted in community networks as these networks are mostly built within “not for profit” projects and do not require enterprise class investment which can lead to inefficient network architectures and routing protocol designs. B.A.T.M.A.N-ADV has been designed as a simple routing protocol that adheres to lightweight equipment requirements of wireless mesh deployment in the rural areas of the developing countries. However, it is built around a flat WMN topology which is challenged with scalability, security and implementation issues; which can limit WMN growth and services expansion. This paper proposes and evaluates the performance of a new multi-layer, multi-protocol WMN architecture that addresses B.A.T.M.A.N-ADV scalability issues by borrowing from wired networks their clustering model and building around the B.A.T.M.A.N Experimental (BMX6) protocol to introduce layer2 tunnelling through a cloud of layer3 routers.
Community healthcare mesh network engineering in white space frequencies
(Institute of Electrical and Electronics Engineers, 2019) Bagula, Antoine
The transition from analog to digital television has availed new spectrum called white space, which can be used to boost the capacity of wireless networks on an opportunistic basis. One sector in which there is a need to use white space frequencies is the healthcare sector
Cyber physical systems dependability using cps-iot monitoring
(MPDI, 2021) Bagula, Antoine; Ajayi, Olasupo; Maluleke, Hloniphani
Recently, vast investments have been made worldwide in developing Cyber-Physical Systems (CPS) as solutions to key socio-economic challenges. The Internet-of-Things (IoT) has also enjoyed widespread adoption, mostly for its ability to add “sensing” and “actuation” capabilities to existing CPS infrastructures. However, attention must be paid to the impact of IoT protocols on the dependability of CPS infrastructures. We address the issues of CPS dependability by using an epidemic model of the underlying dynamics within the CPS’ IoT subsystem (CPS-IoT) and an interferenceaware routing reconfiguration. These help to efficiently monitor CPS infrastructure—avoiding routing oscillation, while improving its safety. The contributions of this paper are threefold. Firstly, a CPS orchestration model is proposed that relies upon: (i) Inbound surveillance and outbound actuation to improve dependability and (ii) a novel information diffusion model that uses epidemic states and diffusion sets to produce diffusion patterns across the CPS-IoT.
Data science for health-care: Patient condition recognition
(University of the Western Cape, 2019) Mandava, Munyaradzi; Bagula, Antoine
The emergence of the Internet of Things (IoT) and Artificial Intelligence (AI) have elicited increased interest in many areas of our daily lives. These include health, agriculture, aviation, manufacturing, cities management and many others. In the health sector, portable vital sign monitoring devices are being developed using the IoT technology to collect patients’ vital signs in real-time. The vital sign data acquired by wearable devices is quantitative and machine learning techniques can be applied to find hidden patterns in the dataset and help the medical practitioner with decision making. There are about 30000 diseases known to man and no human being can possibly remember all of them, their relations to other diseases, their symptoms and whether the symptoms exhibited by the patients are early warnings of a fatal disease. In light of this, Medical Decision Support Systems (MDSS) can provide assistance in making these crucial assessments. In most decision support systems factors a ect each other; they can be contradictory, competitive, and complementary. All these factors contribute to the overall decision and have di erent degrees of influence [85]. However, while there is more need for automated processes to improve the health-care sector, most of MDSS and the associated devices are still under clinical trials. This thesis revisits cyber physical health systems (CPHS) with the objective of designing and implementing a data analytics platform that provides patient condition monitoring services in terms of patient prioritisation and disease identification [1]. Di erent machine learning algorithms are investigated by the platform as potential candidate for achieving patient prioritisation. These include multiple linear regression, multiple logistic regression, classification and regression decision trees, single hidden layer neural networks and deep neural networks. Graph theory concepts are used to design and implement disease identification. The data analytics platform analyses data from biomedical sensors and other descriptive data provided by the patients (this can be recent data or historical data) stored in a cloud which can be private local health Information organisation (LHIO) or belonging to a regional health information organisation (RHIO). Users of the data analytics platform consisting of medical practitioners and patients are assumed to interact with the platform through cities’ pharmacies , rural E-Health kiosks end user applications.
Design and Implementation of a Credible Blockchain-based E-health Records Platform
(University of the Western Cape, 2020) Xu, Lingyu; Bagula, Antoine
With the development of information and network technologies, Electronic Health Records (EHRs) management system has gained wide spread application in managing medical records. One of the major challenges of EHRs is the independent nature of medical institutions. This non-collaborative nature puts a significant barrier between patients, doctors, medical researchers and medical data. Moreover, unlike the unique and strong anti-tampering nature of traditional paper-based records, electronic health records stored in centralization database are vulnerable to risks from network attacks, forgery and tampering. In view of the data sharing difficulties and information security problems commonly found in existing EHRs, this dissertation designs and develops a credible Blockchain-based electronic health records (CB-EHRs) management system. To improve security, the proposed system combines digital signature (using MD5 and RSA) with Role-Based Access Control (RBAC). The advantages of these are strong anti-tampering, high stability, high security, low cost, and easy implementation. To test the efficacy of the system, implementation was done using Java web programming technology. Tests were carried out to determine the efficiency of the Delegated Byzantine Fault Tolerance (dBFT) consensus algorithm, functionality of the RBAC mechanism and the various system modules. Results obtained show that the system can manage and share EHRs safely and effectively. The expectation of the author is that the output of this research would foster the development and adaptation of EHRs management system.
Design and implementation of a credible blockchain-based e-health records platform
(University of Western Cape, 2020) Xu, Lingyu; Bagula, Antoine; Isafiade, Omowunmi
With the development of information and network technologies, Electronic Health Records (EHRs) management system has gained wide spread application in managing medical records. One of the major challenges of EHRs is the independent nature of medical institutions. This non-collaborative nature puts a significant barrier between patients, doctors, medical researchers and medical data. Moreover, unlike the unique and strong anti-tampering nature of traditional paper-based records, electronic health records stored in centralization database are vulnerable to risks from network attacks, forgery and tampering. In view of the data sharing difficulties and information security problems commonly found in existing EHRs, this dissertation designs and develops a credible Blockchain-based electronic health records (CB-EHRs) management system.
An economic feasibility model for sustainable 5G networks in rural dwellings of South Africa
(MDPI, 2022) Maluleke, Hloniphani; Bagula, Antoine; Ajayi, Olasupo
Numerous factors have shown Internet-based technology to be a key enabler in achieving the sustainable development goals (SDG), as well as narrowing the divide between the global north and south. For instance, smart farming, remote/online learning, and smart grids can be used to, respectively, address SDGs 1 and 2 (ending poverty and hunger), 3 (quality education), and 7 and 9 (energy and infrastructure development). Though such Internet-based solutions are commonplace in the global north, they are missing or sparsely available in global south countries. This is due to several factors including underdevelopment, which dissuades service providers from investing heavily in infrastructure for providing capable Internet solutions such as 5G networks in these regions. This paper presents a study conducted to evaluate the feasibility of deploying 5G networks in the rural dwellings of South Africa at affordable rates, which would then serve as a pre-cursor for deploying solutions to improve lives and achieve the SDGs.
Improving quality-of-service in cloud/fog computing through efficient resource allocation
(MPDI, 2019) Akintoye, Samson Busuyi; Bagula, Antoine
Recently, a massive migration of enterprise applications to the cloud has been recorded in the IT world. One of the challenges of cloud computing is Quality-of-Service management, which includes the adoption of appropriate methods for allocating cloud-user applications to virtual resources, and virtual resources to the physical resources. The effective allocation of resources in cloud data centers is also one of the vital optimization problems in cloud computing, particularly when the cloud service infrastructures are built by lightweight computing devices. In this paper, we formulate and present the task allocation and virtual machine placement problems in a single cloud/fog computing environment, and propose a task allocation algorithmic solution and a Genetic Algorithm Based Virtual Machine Placement as solutions for the task allocation and virtual machine placement problem models. Finally, the experiments are carried out and the results show that the proposed solutions improve Quality-of-Service in the cloud/fog computing environment in terms of the allocation cost.
Internet-Of-Things for Cyber Healthcare (L0t4c): Information Dissemination, systems' Interoperability and security
(University of the Western Cape, 2017) Lubamba, Claude kakoko; Bagula, Antoine
Cyber Healthcare is becoming one of the fastest growing industries in the world due to an increasing elderly population and a more health conscious word population. On the other hand, IoT devices are emerging from niche areas to provide new services that we could not fathom without the technological advances made in IoT and healthcare elds [1]. Wireless Sensor Networking (WSN) is a promising approach to cyber healthcare as it can enable real-time monitoring of patients and early detection of emergency conditions and diseases [2, 3]. However, there are a number of issues that need to be addressed in order to bene t from the cyber healthcare promises.
On the design of smart parking networks in the smart cities: an optimal sensor placement model
(MDPI, 2015) Bagula, Antoine; Castelli, Lorenzo
Smart parking is a typical IoT application that can benefit from advances in sensor, actuator and RFID technologies to provide many services to its users and parking owners of a smart city. This paper considers a smart parking infrastructure where sensors are laid down on the parking spots to detect car presence and RFID readers are embedded into parking gates to identify cars and help in the billing of the smart parking. Both types of devices are endowed with wired and wireless communication capabilities for reporting to a gateway where the situation recognition is performed. The sensor devices are tasked to play one of the three roles: (1) slave sensor nodes located on the parking spot to detect car presence/absence; (2) master nodes located at one of the edges of a parking lot to detect presence and collect the sensor readings from the slave nodes; and (3) repeater sensor nodes, also called ''anchor'' nodes, located strategically at specific locations in the parking lot to increase the coverage and connectivity of the wireless sensor network. While slave and master nodes are placed based on geographic constraints, the optimal placement of the relay/anchor sensor nodes in smart parking is an important parameter upon which the cost and e ciency of the parking system depends. We formulate the optimal placement of sensors in smart parking as an integer linear programming multi-objective problem optimizing the sensor network engineering e ciency in terms of coverage and lifetime maximization, as well as its economic gain in terms of the number of sensors deployed for a specific coverage and lifetime. We propose an exact solution to the node placement problem using single-step and two-step solutions implemented in the Mosel language based on the Xpress-MPsuite of libraries. Experimental results reveal the relative e ciency of the single-step compared to the two-step model on di erent performance parameters. These results are consolidated by simulation results, which reveal that our solution outperforms a random placement in terms of both energy consumption, delay and throughput achieved by a smart parking network.
Scalable Wireless Mesh Networks
(University of the Western Cape, 2016) Abdalla, Taha; Bagula, Antoine
Wireless Mesh Networks (WMNs) are wireless multi-hop networks built on wireless nodes that operate in an Independent Basic Set Identifier (IBSS) mode of the IEEE 208.11 wireless standard. IBSS is well known as an ad hoc mode which is found to build ad hoc wireless networks with the aid of routing protocols crafted to work in this mode. Ad hoc wireless mesh networks are always described as self-healing, self-configuring, easy to build, etc. However, these features do come at a cost because a WMN suffers performance degradation and scalability issues, which mainly come from the underlying IBSS mode that is used to form the physical network. Furthermore this is exacerbated by routing protocols in the upper layers which are intended to form a flat network architecture. Partitioning or clustering the flat network into smaller units has been proven to be a viable mechanism to counter the scalability problem in the communication network. The wired network for instance, presents a segmented, hierarchical architecture, where end user devices are organized in virtual local area networks (VLANs) using Ethernet switches and then Routers aggregate multiple VLANs. This thesis develops and evaluates a heterogeneous, clustering architecture to enhance WMN scalability and management. In the proposed architecture, the clustering is separated from the routing, where the clustering is done at the physical layer. At the routing level, each cluster is configured as a WMN using layer 2 routing for intra-cluster routing, and layer 3 routing for inter-domain routing between clusters. Prototypes for the proposed architecture have been built in a laboratory testbed. The proposed architecture reported better scalability and performance results compared to the traditional flat architecture.
Service-aware clustering: an energy-efficient model for the internet-of-things
(MDPI, 2016) Bagula, Antoine; Philip, A.
Current generation wireless sensor routing algorithms and protocols have been designed based on a myopic routing approach, where the motes are assumed to have the same sensing and communication capabilities. Myopic routing is not a natural fit for the IoT, as it may lead to energy imbalance and subsequent short-lived sensor networks, routing the sensor readings over the most service-intensive sensor nodes, while leaving the least active nodes idle. This paper revisits the issue of energy efficiency in sensor networks to propose a clustering model where sensor devices' service delivery is mapped into an energy awareness model, used to design a clustering algorithm that finds service-aware clustering (SAC) configurations in IoT settings. The performance evaluation reveals the relative energy efficiency of the proposed SAC algorithm compared to related routing algorithms in terms of energy consumption, the sensor nodes' life span and its traffic engineering efficiency in terms of throughput and delay. These include the well-known low energy adaptive clustering hierarchy (LEACH) and LEACH-centralized (LEACH-C) algorithms, as well as the most recent algorithms, such as DECSA and MOCRN.
Smart cities air pollution monitoring system - Developing a potential data collecting platform based on Raspberry Pi
(University of the Western Cape, 2019) Chen, Shu; Bagula, Antoine
Air pollution is becoming a challenging issue in our daily lives due to advanced industrialization. This thesis presents a solution to collection and dissemination of pollution data. Most of the devices that monitor air quality are costly and have limited features. The aim of this study is to revisit the issue of pollution in cities with the aim of providing a cheaper and scalable solution to the challenge of pollution data collection and dissemination. The solution proposed in this paper uses Raspberry Pi and Arduino micro-controller boards as the foundation, combined with specific sensors to facilitate the collection and transfer of pollution data reliably and effectively. While most traditional air pollution monitoring equipment and similar projects use memory cards as a medium for data storage, the system proposed in this research is built around a new network selection model that transfers data to the server by using either Bluetooth, Wi-Fi, GSM, or the LoRa protocol. The connectivity protocol is selected automatically and opportunistically by the network selection algorithm defined in the micro-controller board. The final data will be presented to the user through a mobile application and website interface effectively and intuitively after being processed in the server. This data transfer system can effectively reduce the cost and input of human resources. It is a viable solution. For other environmental research, this system can provide an air quality data support for analysis and reference. Modularity and cost-effectiveness are fully considered when designing the system. It is a viable solution. We can generalize the system by slightly changing the data transmission modules. In other case, it can be used as a platform for similar data transmission and offer help for other research directions.
Smart renewable energy : architectures, dimensioning and monitoring
(University of the Western Cape, 2017) Erasmus, Zenville; Bagula, Antoine
The Smart Renewable Energy project at the University of The Western Cape, under the guidance of the Intelligent Systems and Advanced Telecommunication (ISAT) group, aims at developing a dynamic system that enables users to (1) design smart architectures for next generation wind and solar systems to meet African power challenges (2) use these architectures to dimension the underlying solar and wind power systems and (3) simulate, implement and evaluate the performance of such power systems. The project's existing web and mobile monitoring system will undergo a much needed upgrade to cater for monitoring of the existing system's environmental and battery bank parameters. This will be implemented by allowing users to monitor input, storage and output trends over various time frames. These time frames would include hourly, daily, weekly and monthly readings. The visual evaluation of the system will be generated by mathematical, statistical and machine learning techniques. Trends will be discovered that will allow users to optimize the system's efficiency and their usage patterns. The accompanied dimensioning system will allow users to cater for their needs in a two way fashion. Users will be able to specify the number of devices that they want to run from a solar or wind based system and their power needs will be generated. They will also be able to determine what a given system is capable of producing and the number of devices that can be used simultaneously, as a result.

Browsing by Author "Bagula, Antoine"

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