Imed Ben Dhaou - Academia.edu (original) (raw)

Papers by Imed Ben Dhaou

Electronics

In the era of the Fourth Industrial Revolution, cybercriminals are targeting critical infrastruct... more In the era of the Fourth Industrial Revolution, cybercriminals are targeting critical infrastructures such as traffic light systems and smart grids. A major concern is the security of such systems, which can be broken down into a number of categories, such as the authentication of data collection devices, secure data transmission, and use of the data by authorized and authenticated parties. The majority of research studies in the literature have largely focused on data integrity and user authentication. So far, no published work has addressed the security of a traffic light system from data collection to data access. Furthermore, it is evident that the conventional cloud computing architecture is incapable of analyzing and managing the massive amount of generated data. As a result, the fog computing paradigm combined with blockchain technology may be the best way to ensure data privacy in a decentralized manner while reducing overheads, latency, and maintaining security. This paper ...

2019 IEEE PES/IAS PowerAfrica

The depletion of water table coupled with the decrease in rainfall due to climate change has push... more The depletion of water table coupled with the decrease in rainfall due to climate change has pushed international communities to look for better ways to save water. Furthermore, access to the water table in disconnected communities in off-grid locations is a challenge to many African countries. These challenges negatively affect farming activities where irrigation plays an important role. In this paper, we propose a sustainable and smart DC microgrid irrigation system using multi-agent systems along with Internet of Things technologies. The system is composed of a microgrid connected water pumping system and Internet of Things enabled sensors for irrigation. An algorithm that uses an agent-based approach to regulate energy demand from the PV system and controls irrigation is also introduced. The features of the proposed system have been compared against features for related systems.

Cluster Computing, 2022

Several applications have emerged with the proliferation of mobile devices to provide communicati... more Several applications have emerged with the proliferation of mobile devices to provide communication, learning, social networking, entertainment, and community computing services. Such applications include augmented reality, online gaming, and other real-time applications that need higher computational resources. These applications, executing on mobile devices, often need to access external computing resources and offload the application tasks to the cloud or mobile edge computing (MEC) servers. However, delivering task offloading results to the users in the MEC environment is a challenge, certainly when user mobility is high. Sub-optimal server selection at the offloading stage increases latency, energy consumption and deteriorates both quality of experience and quality of service. Existing techniques proposed in the literature handle computation offloading and mobility management separately. Without considering the real-time mobility factors, the solutions produced are sub-optimal. Some solutions exist to manage mobility, but they involve higher time complexity. We consider the user mobility in offloading decisions and present a lightweight mobility prediction and offloading (LiMPO) framework that offloads the compute-intensive tasks to the predicted user location using artificial neural networks with less complexity. In addition, we propose a multi-objective genetic algorithm based server selection technique that jointly optimizes latency and energy consumption while improving the resource utilization of MEC servers. The performance of the proposed framework is compared with two other techniques task-assignment with optimized mobility and dynamic mobility-aware offloading algorithm for edge computing. The simulation results show that LiMPO outperforms the others by latency reduction, energy efficiency, and enhanced resource utilization.

2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019

This DOI was registered to an article that was not presented by the author(s) at this conference.... more This DOI was registered to an article that was not presented by the author(s) at this conference. As per section 8.2.1.B.13 of IEEE's "Publication Services and Products Board Operations Manual," IEEE has chosen to exclude this article from distribution. We regret any inconvenience.

2020 6th IEEE International Energy Conference (ENERGYCon), 2020

The smart grid is a new revolution in the energy sector in which information and communication sy... more The smart grid is a new revolution in the energy sector in which information and communication system is integrated within the conventional electric power generation and distribution system. A key component of this system is the Advanced Metering Infrastructure (AMI), which enables two-way communication between consumer and utility company via a smart meter. In the smart home energy management system (SHEMS), the smart meter is commissioned to monitor, control, trade, and log the energy consumption. Due to the diversification of the appliances in SHEMS, manufactured by different vendors with uncommon standards and deregulation of the communication protocol, then applications and devices in SHEMS become difficult to interoperate. With IoT invention, the smart meter should be able to address the heterogeneity issues. This paper propose an IoT smart meter architecture that addresses the heterogeneity problem in SHEMS by making use of middleware platform which solves interoperability problem in any IoT scenarios. A prototype system using Raspberry Pi and Kaa IoT middleware is reported.

2019 IST-Africa Week Conference (IST-Africa), 2019

The iGrid project deals with the design and implementation of a solarpowered smart microgrid to s... more The iGrid project deals with the design and implementation of a solarpowered smart microgrid to supply electric power to small rural communities. In this paper, we discuss the roadmap of the iGrid project, which forms by merging the roadmaps of KIC (knowledge and Innovation Community) and CDE (Challenge-Driven Education). We introduce and explain a five-gear chain as Challenge, Education, Research, Innovation, and Deployment, called CERID, to reach the main goals of this project. We investigate the full chain in the iGrid project, which is established between KTH Royal Institute of Technology (Sweden) and University of Dar es Salam (Tanzania). We introduce the key stakeholders and explain how CERID goals can be accomplished in higher educations and through scientific research. Challenges are discussed, some innovative ideas are introduced and deployment solutions are recommended.

EDULEARN17 Proceedings, Mar 1, 2017

Due to changes in the market positions of old companies caused by innovation in technologies, ser... more Due to changes in the market positions of old companies caused by innovation in technologies, services, business concepts and global challenges faced by nations in terms of climate and safety, academic systems in Europe have started to look into new pedagogical models and strategic partnerships. The new systems that connect research, education and innovation can offer unique opportunities to explore different solutions that were not possible before. In this paper, we present concrete experiences and directions for creating innovative learning environments with stronger impact and excitement to all stakeholder involved. We describe a new approach that relies on three fundamental concepts: strong commitment and support of open science, challenge driven education model and physical co-location of partners. We give examples of applications of this approach and discuss various aspects that are involved.

2019 IST-Africa Week Conference (IST-Africa), 2019

To improve the living standard of urban communities and to render the healthcare services sustain... more To improve the living standard of urban communities and to render the healthcare services sustainable and efficient, e-health system is experiencing a paradigm shift. Patients with cognitive discrepancies can be monitored and observed through the analyses of power consumption of home appliances. This paper surveys recent trends in home-based e-health services using metered energy consumption data. It also analyses and summarizes the constant impedance, constant current and constant power (ZIP) approaches for load modelling. The analysis briefly recaptures both non-intrusive and intrusive techniques. The work reports an architecture using IoT technologies for the design of a smart-meter, and fog-computing paradigm for raw processing of energy dataset. Finally, the paper describes the implementation platform based on GirdLAB-D simulation to construct accurate models of household appliances and test the machine-learning algorithm for the detection of abnormal behaviour.

International Journal of Smart Grid and Clean Energy, 2019

The increasing interest in integrating renewable energies source has raised concerns about contro... more The increasing interest in integrating renewable energies source has raised concerns about control operations. The presence of new energy sources, distributed storage, power electronic devices and communication links make a power system's control and monitoring more complex and adaptive than ever before. Recently, the use of agentbased distributed control has seen to have a significant impact on the grid and microgrid controls. The load-shedding technique is among the features used to balance the power consumption in the power system upon less power production. Towards achieving these, different mechanisms, algorithms, challenges, and approaches have been developed and hence need to be reviewed and integrated from the system solution perspective. This research focuses on the review of the state-of-the-art load-shedding techniques, whereby the focus is on control algorithms, simulation platforms and integrations, and control devices for DC microgrid. The research also investigates open issues and challenges that need further investigations. The analyses reported in the paper upholds the importance of the distributed multi-agent system, MAS, in implementing distinct control operations including load-shedding. The effectiveness of the control operations using MAS rely on low-latency and secure communication links in which IoT has been branded as a promising technology for implementing distributed MAS

EDULEARN proceedings, 2017

The need for creative engineers using natural sciences as their approach has not drastically chan... more The need for creative engineers using natural sciences as their approach has not drastically changed in the past 100 years. However, technology advances have created new challenges and brought new ...

Journal of Cloud Computing, Aug 30, 2022

Cloud technology is not immune to bugs and issue tracking. A dedicated system is required that wi... more Cloud technology is not immune to bugs and issue tracking. A dedicated system is required that will extremely error prone and less cumbersome and must command a high degree of collaboration, flexibility of operations and smart decision making. One of the primary goals of software engineering is to provide high-quality software within a specified budget and period for cloud-based technology. However, defects found in Cloud-Based Bug Tracking software's can result in quality reduction as well as delay in the delivery process. Therefore, software testing plays a vital role in ensuring the quality of software in the cloud, but software testing requires higher time and cost with the increase of complexity of user requirements. This issue is even cumbersome in the embedded software design. Early detection of defect-prone components in general and embedded software helps to recognize which components require higher attention during testing and thereby allocate the available resources effectively and efficiently. This research was motivated by the demand of minimizing the time and cost required for Cloud-Based Bug Tracking Software testing for both embedded and general-purpose software while ensuring the delivery of high-quality software products without any delays emanating from the cloud. Not withstanding that several machine learning techniques have been widely applied for building software defect prediction models in general, achieving higher prediction accuracy is still a challenging task. Thus, the primary aim of this research is to investigate how deep learning methods can be used for Cloud-Based Bug Tracking Software defect detection with a higher accuracy. The research conducted an experiment with four different configurations of Multi-Layer Perceptron neural network using five publicly available software defect datasets. Results of the experiments show that the best possible network configuration for software defect detection model using Multi-Layer Perceptron can be the prediction model with two hidden layers having 25 neurons in the first hidden layer and 5 neurons in the second hidden layer.

Sensors

An expert performs bone fracture diagnosis using an X-ray image manually, which is a time-consumi... more An expert performs bone fracture diagnosis using an X-ray image manually, which is a time-consuming process. The development of machine learning (ML), as well as deep learning (DL), has set a new path in medical image diagnosis. In this study, we proposed a novel multi-scale feature fusion of a convolution neural network (CNN) and an improved canny edge algorithm that segregate fracture and healthy bone image. The hybrid scale fracture network (SFNet) is a novel two-scale sequential DL model. This model is highly efficient for bone fracture diagnosis and takes less computation time compared to other state-of-the-art deep CNN models. The innovation behind this research is that it works with an improved canny edge algorithm to obtain edges in the images that localize the fracture region. After that, grey images and their corresponding canny edge images are fed to the proposed hybrid SFNet for training and evaluation. Furthermore, the performance is also compared with the state-of-the-...

Water

The detection of water bodies from satellite images plays a vital role in research development. I... more The detection of water bodies from satellite images plays a vital role in research development. It has a wide range of applications such as the prediction of natural disasters and detecting drought and flood conditions. There were few existing applications that focused on detecting water bodies that are becoming extinct in nature. The dataset to train this deep learning model is taken from Kaggle. It has two classes, namely water bodies and masks. There is a total of 2841 sentinel-2 satellite images with corresponding 2841 masks. Additionally, the present work focuses on using UNet, Tensorflow to detect the water bodies. It uses a Nadam optimizer to reduce the losses. It also finds best-optimized parameters for the activation function, a number of nodes in each layer. This proposed model achieves integrity by embedding a security feature Elliptic Curve Digital Signature Algorithm (ECDSA). It generates a digital signature for the predicted area of water bodies which helps to secure t...

Sensors

The Internet of Vehicles (IoV) is a new paradigm for vehicular networks. Using diverse access met... more The Internet of Vehicles (IoV) is a new paradigm for vehicular networks. Using diverse access methods, IoV enables vehicles to connect with their surroundings. However, without data security, IoV settings might be hazardous. Because of the IoV’s openness and self-organization, they are prone to malevolent attack. To overcome this problem, this paper proposes a revolutionary blockchain-enabled game theory-based authentication mechanism for securing IoVs. Here, a three layer multi-trusted authorization solution is provided in which authentication of vehicles can be performed from initial entry to movement into different trusted authorities’ areas without any delay by the use of Physical Unclonable Functions (PUFs) in the beginning and later through duel gaming, and a dynamic Proof-of-Work (dPoW) consensus mechanism. Formal and informal security analyses justify the framework’s credibility in more depth with mathematical proofs. A rigorous comparative study demonstrates that the sugges...

2020 6th IEEE International Energy Conference (ENERGYCon)

Demand Side Management, DSM, is a program supported by the smart-grid which aims at matching the ... more Demand Side Management, DSM, is a program supported by the smart-grid which aims at matching the energy consumption and production. Several techniques for demandside management have been proposed, including load-shedding, time of use pricing, real-time pricing, and critical peak pricing. In this work, we propose a distributed load-shedding algorithm using the multi-agent system. The agents in residential areas collaborate to reduce the energy demands using various forecasting techniques. The computational distributed framework is provided via fog computing to minimize power consumption, costs, and latency when designed using LoRaWAN protocol.

2018 IST-Africa Week Conference (IST-Africa), 2018

The research projects in ICT need to embrace new dimensions. Traditionally, research group work i... more The research projects in ICT need to embrace new dimensions. Traditionally, research group work in an isolated manner and is conducted in a purely academic way. This type of research is outdated and needs to be more innovative, engaging and address societal challenges from the local perspective. Quadruple-helix model is a concept that ties together government, academia, industry, and society to promote innovation in education. Challenge drive education is a graduate course that aims to solve societal problems in the quadruple-helix model. This paper summarizes the key idea of challenge driven education to design an intelligent dc microgrid for rural areas of Tanzania.

2021 18th International Multi-Conference on Systems, Signals & Devices (SSD), 2021

This paper advocates a secure sensor node for IoT-enabled traffic light system. The node is compo... more This paper advocates a secure sensor node for IoT-enabled traffic light system. The node is composed of a magnetoresistive sensor, a microcontroller, and a communication module. The sensor node communicates with the traffic light controller using the Zigbee protocol. The system can also count the number of the vehicle to determine the level of service. The sensor node uses an elliptic curve digital signature algorithm for secure communication with the traffic light controller. The implementation results show that the system has a latency of less than 1.4 sec and resilient to side-channel attack using the secp160r1 curve parameters. The system consumes on average 148 mW at 3.3V.

ISCAS 2001. The 2001 IEEE International Symposium on Circuits and Systems (Cat. No.01CH37196)

New technique for low-power characterization of arithmetic units in Deep-submicron CMOS technolog... more New technique for low-power characterization of arithmetic units in Deep-submicron CMOS technology is proposed. The core of this technique is based on a proper transformation of the input pattern in order to improve fit and prediction of the power consumption. The transformation is also useful in reducing the complexity associated with the characterization process without sacrificing the accuracy of the estimators. In this paper, the entropy of the input pattern is proposed as a transformation technique. An algorithm, called LP-DSM, for library characterization based on entropy of the input pattern is derived. The LP-DSM takes into account the glitch power consumption. LP-DSM algorithm has been used to characterize the power consumption of several arithmetic units implemented, using full-custom design, in 0. 3 5 p n. 3.3V CMOS process. Under the real delay model, the extensive numerical results have showed that the average error of LP-DSM is less than 16% compared to spice results. Also, the results have showed that LP-DSM is very robust to the variations in the statistics of the input pattern.

Electronics

In the era of the Fourth Industrial Revolution, cybercriminals are targeting critical infrastruct... more In the era of the Fourth Industrial Revolution, cybercriminals are targeting critical infrastructures such as traffic light systems and smart grids. A major concern is the security of such systems, which can be broken down into a number of categories, such as the authentication of data collection devices, secure data transmission, and use of the data by authorized and authenticated parties. The majority of research studies in the literature have largely focused on data integrity and user authentication. So far, no published work has addressed the security of a traffic light system from data collection to data access. Furthermore, it is evident that the conventional cloud computing architecture is incapable of analyzing and managing the massive amount of generated data. As a result, the fog computing paradigm combined with blockchain technology may be the best way to ensure data privacy in a decentralized manner while reducing overheads, latency, and maintaining security. This paper ...

2019 IEEE PES/IAS PowerAfrica

The depletion of water table coupled with the decrease in rainfall due to climate change has push... more The depletion of water table coupled with the decrease in rainfall due to climate change has pushed international communities to look for better ways to save water. Furthermore, access to the water table in disconnected communities in off-grid locations is a challenge to many African countries. These challenges negatively affect farming activities where irrigation plays an important role. In this paper, we propose a sustainable and smart DC microgrid irrigation system using multi-agent systems along with Internet of Things technologies. The system is composed of a microgrid connected water pumping system and Internet of Things enabled sensors for irrigation. An algorithm that uses an agent-based approach to regulate energy demand from the PV system and controls irrigation is also introduced. The features of the proposed system have been compared against features for related systems.

Cluster Computing, 2022

Several applications have emerged with the proliferation of mobile devices to provide communicati... more Several applications have emerged with the proliferation of mobile devices to provide communication, learning, social networking, entertainment, and community computing services. Such applications include augmented reality, online gaming, and other real-time applications that need higher computational resources. These applications, executing on mobile devices, often need to access external computing resources and offload the application tasks to the cloud or mobile edge computing (MEC) servers. However, delivering task offloading results to the users in the MEC environment is a challenge, certainly when user mobility is high. Sub-optimal server selection at the offloading stage increases latency, energy consumption and deteriorates both quality of experience and quality of service. Existing techniques proposed in the literature handle computation offloading and mobility management separately. Without considering the real-time mobility factors, the solutions produced are sub-optimal. Some solutions exist to manage mobility, but they involve higher time complexity. We consider the user mobility in offloading decisions and present a lightweight mobility prediction and offloading (LiMPO) framework that offloads the compute-intensive tasks to the predicted user location using artificial neural networks with less complexity. In addition, we propose a multi-objective genetic algorithm based server selection technique that jointly optimizes latency and energy consumption while improving the resource utilization of MEC servers. The performance of the proposed framework is compared with two other techniques task-assignment with optimized mobility and dynamic mobility-aware offloading algorithm for edge computing. The simulation results show that LiMPO outperforms the others by latency reduction, energy efficiency, and enhanced resource utilization.

2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019

This DOI was registered to an article that was not presented by the author(s) at this conference.... more This DOI was registered to an article that was not presented by the author(s) at this conference. As per section 8.2.1.B.13 of IEEE's "Publication Services and Products Board Operations Manual," IEEE has chosen to exclude this article from distribution. We regret any inconvenience.

2020 6th IEEE International Energy Conference (ENERGYCon), 2020

The smart grid is a new revolution in the energy sector in which information and communication sy... more The smart grid is a new revolution in the energy sector in which information and communication system is integrated within the conventional electric power generation and distribution system. A key component of this system is the Advanced Metering Infrastructure (AMI), which enables two-way communication between consumer and utility company via a smart meter. In the smart home energy management system (SHEMS), the smart meter is commissioned to monitor, control, trade, and log the energy consumption. Due to the diversification of the appliances in SHEMS, manufactured by different vendors with uncommon standards and deregulation of the communication protocol, then applications and devices in SHEMS become difficult to interoperate. With IoT invention, the smart meter should be able to address the heterogeneity issues. This paper propose an IoT smart meter architecture that addresses the heterogeneity problem in SHEMS by making use of middleware platform which solves interoperability problem in any IoT scenarios. A prototype system using Raspberry Pi and Kaa IoT middleware is reported.

2019 IST-Africa Week Conference (IST-Africa), 2019

The iGrid project deals with the design and implementation of a solarpowered smart microgrid to s... more The iGrid project deals with the design and implementation of a solarpowered smart microgrid to supply electric power to small rural communities. In this paper, we discuss the roadmap of the iGrid project, which forms by merging the roadmaps of KIC (knowledge and Innovation Community) and CDE (Challenge-Driven Education). We introduce and explain a five-gear chain as Challenge, Education, Research, Innovation, and Deployment, called CERID, to reach the main goals of this project. We investigate the full chain in the iGrid project, which is established between KTH Royal Institute of Technology (Sweden) and University of Dar es Salam (Tanzania). We introduce the key stakeholders and explain how CERID goals can be accomplished in higher educations and through scientific research. Challenges are discussed, some innovative ideas are introduced and deployment solutions are recommended.

EDULEARN17 Proceedings, Mar 1, 2017

Due to changes in the market positions of old companies caused by innovation in technologies, ser... more Due to changes in the market positions of old companies caused by innovation in technologies, services, business concepts and global challenges faced by nations in terms of climate and safety, academic systems in Europe have started to look into new pedagogical models and strategic partnerships. The new systems that connect research, education and innovation can offer unique opportunities to explore different solutions that were not possible before. In this paper, we present concrete experiences and directions for creating innovative learning environments with stronger impact and excitement to all stakeholder involved. We describe a new approach that relies on three fundamental concepts: strong commitment and support of open science, challenge driven education model and physical co-location of partners. We give examples of applications of this approach and discuss various aspects that are involved.

2019 IST-Africa Week Conference (IST-Africa), 2019

To improve the living standard of urban communities and to render the healthcare services sustain... more To improve the living standard of urban communities and to render the healthcare services sustainable and efficient, e-health system is experiencing a paradigm shift. Patients with cognitive discrepancies can be monitored and observed through the analyses of power consumption of home appliances. This paper surveys recent trends in home-based e-health services using metered energy consumption data. It also analyses and summarizes the constant impedance, constant current and constant power (ZIP) approaches for load modelling. The analysis briefly recaptures both non-intrusive and intrusive techniques. The work reports an architecture using IoT technologies for the design of a smart-meter, and fog-computing paradigm for raw processing of energy dataset. Finally, the paper describes the implementation platform based on GirdLAB-D simulation to construct accurate models of household appliances and test the machine-learning algorithm for the detection of abnormal behaviour.

International Journal of Smart Grid and Clean Energy, 2019

The increasing interest in integrating renewable energies source has raised concerns about contro... more The increasing interest in integrating renewable energies source has raised concerns about control operations. The presence of new energy sources, distributed storage, power electronic devices and communication links make a power system's control and monitoring more complex and adaptive than ever before. Recently, the use of agentbased distributed control has seen to have a significant impact on the grid and microgrid controls. The load-shedding technique is among the features used to balance the power consumption in the power system upon less power production. Towards achieving these, different mechanisms, algorithms, challenges, and approaches have been developed and hence need to be reviewed and integrated from the system solution perspective. This research focuses on the review of the state-of-the-art load-shedding techniques, whereby the focus is on control algorithms, simulation platforms and integrations, and control devices for DC microgrid. The research also investigates open issues and challenges that need further investigations. The analyses reported in the paper upholds the importance of the distributed multi-agent system, MAS, in implementing distinct control operations including load-shedding. The effectiveness of the control operations using MAS rely on low-latency and secure communication links in which IoT has been branded as a promising technology for implementing distributed MAS

EDULEARN proceedings, 2017

The need for creative engineers using natural sciences as their approach has not drastically chan... more The need for creative engineers using natural sciences as their approach has not drastically changed in the past 100 years. However, technology advances have created new challenges and brought new ...

Journal of Cloud Computing, Aug 30, 2022

Cloud technology is not immune to bugs and issue tracking. A dedicated system is required that wi... more Cloud technology is not immune to bugs and issue tracking. A dedicated system is required that will extremely error prone and less cumbersome and must command a high degree of collaboration, flexibility of operations and smart decision making. One of the primary goals of software engineering is to provide high-quality software within a specified budget and period for cloud-based technology. However, defects found in Cloud-Based Bug Tracking software's can result in quality reduction as well as delay in the delivery process. Therefore, software testing plays a vital role in ensuring the quality of software in the cloud, but software testing requires higher time and cost with the increase of complexity of user requirements. This issue is even cumbersome in the embedded software design. Early detection of defect-prone components in general and embedded software helps to recognize which components require higher attention during testing and thereby allocate the available resources effectively and efficiently. This research was motivated by the demand of minimizing the time and cost required for Cloud-Based Bug Tracking Software testing for both embedded and general-purpose software while ensuring the delivery of high-quality software products without any delays emanating from the cloud. Not withstanding that several machine learning techniques have been widely applied for building software defect prediction models in general, achieving higher prediction accuracy is still a challenging task. Thus, the primary aim of this research is to investigate how deep learning methods can be used for Cloud-Based Bug Tracking Software defect detection with a higher accuracy. The research conducted an experiment with four different configurations of Multi-Layer Perceptron neural network using five publicly available software defect datasets. Results of the experiments show that the best possible network configuration for software defect detection model using Multi-Layer Perceptron can be the prediction model with two hidden layers having 25 neurons in the first hidden layer and 5 neurons in the second hidden layer.

Sensors

An expert performs bone fracture diagnosis using an X-ray image manually, which is a time-consumi... more An expert performs bone fracture diagnosis using an X-ray image manually, which is a time-consuming process. The development of machine learning (ML), as well as deep learning (DL), has set a new path in medical image diagnosis. In this study, we proposed a novel multi-scale feature fusion of a convolution neural network (CNN) and an improved canny edge algorithm that segregate fracture and healthy bone image. The hybrid scale fracture network (SFNet) is a novel two-scale sequential DL model. This model is highly efficient for bone fracture diagnosis and takes less computation time compared to other state-of-the-art deep CNN models. The innovation behind this research is that it works with an improved canny edge algorithm to obtain edges in the images that localize the fracture region. After that, grey images and their corresponding canny edge images are fed to the proposed hybrid SFNet for training and evaluation. Furthermore, the performance is also compared with the state-of-the-...

Water

The detection of water bodies from satellite images plays a vital role in research development. I... more The detection of water bodies from satellite images plays a vital role in research development. It has a wide range of applications such as the prediction of natural disasters and detecting drought and flood conditions. There were few existing applications that focused on detecting water bodies that are becoming extinct in nature. The dataset to train this deep learning model is taken from Kaggle. It has two classes, namely water bodies and masks. There is a total of 2841 sentinel-2 satellite images with corresponding 2841 masks. Additionally, the present work focuses on using UNet, Tensorflow to detect the water bodies. It uses a Nadam optimizer to reduce the losses. It also finds best-optimized parameters for the activation function, a number of nodes in each layer. This proposed model achieves integrity by embedding a security feature Elliptic Curve Digital Signature Algorithm (ECDSA). It generates a digital signature for the predicted area of water bodies which helps to secure t...

Sensors

The Internet of Vehicles (IoV) is a new paradigm for vehicular networks. Using diverse access met... more The Internet of Vehicles (IoV) is a new paradigm for vehicular networks. Using diverse access methods, IoV enables vehicles to connect with their surroundings. However, without data security, IoV settings might be hazardous. Because of the IoV’s openness and self-organization, they are prone to malevolent attack. To overcome this problem, this paper proposes a revolutionary blockchain-enabled game theory-based authentication mechanism for securing IoVs. Here, a three layer multi-trusted authorization solution is provided in which authentication of vehicles can be performed from initial entry to movement into different trusted authorities’ areas without any delay by the use of Physical Unclonable Functions (PUFs) in the beginning and later through duel gaming, and a dynamic Proof-of-Work (dPoW) consensus mechanism. Formal and informal security analyses justify the framework’s credibility in more depth with mathematical proofs. A rigorous comparative study demonstrates that the sugges...

2020 6th IEEE International Energy Conference (ENERGYCon)

Demand Side Management, DSM, is a program supported by the smart-grid which aims at matching the ... more Demand Side Management, DSM, is a program supported by the smart-grid which aims at matching the energy consumption and production. Several techniques for demandside management have been proposed, including load-shedding, time of use pricing, real-time pricing, and critical peak pricing. In this work, we propose a distributed load-shedding algorithm using the multi-agent system. The agents in residential areas collaborate to reduce the energy demands using various forecasting techniques. The computational distributed framework is provided via fog computing to minimize power consumption, costs, and latency when designed using LoRaWAN protocol.

2018 IST-Africa Week Conference (IST-Africa), 2018

The research projects in ICT need to embrace new dimensions. Traditionally, research group work i... more The research projects in ICT need to embrace new dimensions. Traditionally, research group work in an isolated manner and is conducted in a purely academic way. This type of research is outdated and needs to be more innovative, engaging and address societal challenges from the local perspective. Quadruple-helix model is a concept that ties together government, academia, industry, and society to promote innovation in education. Challenge drive education is a graduate course that aims to solve societal problems in the quadruple-helix model. This paper summarizes the key idea of challenge driven education to design an intelligent dc microgrid for rural areas of Tanzania.

2021 18th International Multi-Conference on Systems, Signals & Devices (SSD), 2021

This paper advocates a secure sensor node for IoT-enabled traffic light system. The node is compo... more This paper advocates a secure sensor node for IoT-enabled traffic light system. The node is composed of a magnetoresistive sensor, a microcontroller, and a communication module. The sensor node communicates with the traffic light controller using the Zigbee protocol. The system can also count the number of the vehicle to determine the level of service. The sensor node uses an elliptic curve digital signature algorithm for secure communication with the traffic light controller. The implementation results show that the system has a latency of less than 1.4 sec and resilient to side-channel attack using the secp160r1 curve parameters. The system consumes on average 148 mW at 3.3V.

ISCAS 2001. The 2001 IEEE International Symposium on Circuits and Systems (Cat. No.01CH37196)

New technique for low-power characterization of arithmetic units in Deep-submicron CMOS technolog... more New technique for low-power characterization of arithmetic units in Deep-submicron CMOS technology is proposed. The core of this technique is based on a proper transformation of the input pattern in order to improve fit and prediction of the power consumption. The transformation is also useful in reducing the complexity associated with the characterization process without sacrificing the accuracy of the estimators. In this paper, the entropy of the input pattern is proposed as a transformation technique. An algorithm, called LP-DSM, for library characterization based on entropy of the input pattern is derived. The LP-DSM takes into account the glitch power consumption. LP-DSM algorithm has been used to characterize the power consumption of several arithmetic units implemented, using full-custom design, in 0. 3 5 p n. 3.3V CMOS process. Under the real delay model, the extensive numerical results have showed that the average error of LP-DSM is less than 16% compared to spice results. Also, the results have showed that LP-DSM is very robust to the variations in the statistics of the input pattern.