simeon Ajakwe - Academia.edu (original) (raw)

Papers by simeon Ajakwe

Advances in systems analysis, software engineering, and high performance computing book series, Jul 12, 2024

Drones, Feb 15, 2022

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Accurate detection of distant drones in clustered environment amidst other flying objects such as... more Accurate detection of distant drones in clustered environment amidst other flying objects such as birds is of critical importance in anti-drone system design. This study proposed a novel object detection model that efficiently detect and differentiate drones from other flying objects under different weather conditions. The custom dataset consists of manually generated drone images and bird samples under sunny, cloudy and evening conditions. The simulation result shows that KITYOLO outperformed YOLOv5 both in precision (sunny 96.2% vs 85%; cloudy 73.7% vs 26.3%; evening 58.5% vs 26.1%) and recall (evening 42.4% vs 15%) in all aspects with an overall F1-score of 98% as against 91.9% while maintaining timeliness and memory usage.

2022 International Conference on Information Networking (ICOIN), Jan 12, 2022

The surging proliferation in the deployment of unmanned aerial vehicles (UAVs) in various domains... more The surging proliferation in the deployment of unmanned aerial vehicles (UAVs) in various domains has resulted into unsolicited intrusion into private properties and protected areas thereby posing threat to national security. This paper proposed an adaptive scenario-based approach for detecting drone invasion using enhanced YOLOv5 deep learning model to detect different drones and identify attached objects operating under any environment, size, speed, or shape. The dataset consists of 6 drone models and 8 attached weapons manually generated and preprocessed to form samples. In terms of accuracy, sensitivity, and timeliness, the result shows that our model achieved superior detection precision of 100%, sensitivity of 99.9%, F1-score of 87.2% for weapons identification at a shorter time of 0. 021s than other models. The high detection accuracy undoubtedly makes our model well suited for real-time drone monitoring and countering of illegal drones in military offensives with minimal resource usage.

IEEE Access, 2022

The future of healthcare relies heavily on the connection of humans to intelligent devices via co... more The future of healthcare relies heavily on the connection of humans to intelligent devices via communication networks for rapid medical response. Hence, the evaluation of the performance of smart wearable devices as veritable tools for prompt, pervasive, and proactive healthcare delivery to end-users in response to socioeconomic dynamics is imperative especially as 5G unwinds and B5G emerges. Despite the boom in the wearable market and significant improvement in communication technologies, the translation of wearable data from clinical trials to valuable assets for practical medical application is burdened with varying challenges. This review provides an introspective analysis of the performance of unobtrusive wearable devices based on identified key performance indicators (KPIs) in relation to evolving generation networks in achieving innovative health care delivery. A total of 2751 articles pooled from 5 digital libraries were screened and 16 were selected for this review using PRISMA. The identified E-DISC wearable KPIs; energy efficiency, discretization, intelligence, secured network, and customizable standards are currently engrossed with both reliability and real-time issues that undermine its performance, perceptibility, and acceptability by end-users. The transformation of smart wearable devices' data from clinical trials into intangible resources for medical application is the fulcrum of innovative healthcare actualization. Further insight on how the identified challenges can be streamlined for smooth device alignment and transition to the emerging B5G network and its eco-friendly environment is also discussed. It is hoped that this will serve as a rallying point for research direction in translating prospective wearable solutions into a valuable resource for actualizing p-health.

Journal of intelligence, conflict and warfare, May 31, 2023

The development of a comprehensive and decisive drone defense integrated control system that can ... more The development of a comprehensive and decisive drone defense integrated control system that can provide maximum security is crucial for maintaining territorial integrity and accelerating smart aerial mobility to sustain the emerging drone transportation system (DTS) for priority-based logistics and mobile communication. This study explores recent developments in the design of robust drone defense control (D D S) systems that can observe and respond not only to drone attacks inside and outside a facility but also to equipment data such as CCTV security control on the ground and security sensors in the facility immediately. Also, it considered DDS strategies, schema, and innovative security setups in different countries. Finally, open research issues in DDS designs are discussed, and useful recommendations are provided. Effective means for drone source authentication, delivery package verification, operator authorization, and dynamic scenario specific engagement are solicited for comprehensive DDS design for maximum security.

The Domain Name System (DNS) is the hub of the cyberspace and communications services which also ... more The Domain Name System (DNS) is the hub of the cyberspace and communications services which also plays enabling role in the Industrial Internet of Things (IIoT) and transmission at large. DNS enciphering in HyperText Transfer Protocol Secure (HTTPS) as DoH did not eliminate vulnerability and intrusion into critical systems. This study proposed a time-efficient Ensemble Learning (EL) model for countering DNS vulnerability to attack. The proposed EL candidate incorporates feature selection capability in extracting relevant features for enhanced model optimization. The simulation results showed that the proposed EL candidate effectively mitigates vulnera-bility, classifying DNS traffic into Non-DoH, Malicious DoH and Benign-DoH. The proposed model outperforms other compared state-of-art EL techniques with a combined advantage of accuracy and training time of 99.5% and 13.96s.

IEEE Internet of Things Journal, Aug 15, 2023

Sensors, Jan 20, 2023

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)

2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)

The Journal of Intelligence, Conflict, and Warfare

The development of a comprehensive and decisive drone defense integrated control system that can ... more The development of a comprehensive and decisive drone defense integrated control system that can provide maximum security is crucial for maintaining territorial integrity and accelerating smart aerial mobility to sustain the emerging drone transportation system (DTS) for priority-based logistics and mobile communication. This study explores recent developments in the design of robust drone defense control systems that can observe and respond not only to drone attacks inside and outside a facility but also to equipment data such as CCTV security control on the ground and security sensors in the facility at a glance. Also, it considered DDS strategies, schema, and innovative security setups in different regions. Finally, open research issues in DDs designs are discussed, and useful recommendations are provided. Effective means for drone source authentication, delivery package verification, operator authorization, and dynamic scenario-specific engagement are solicited for comprehensive...

IEEE Internet of Things Journal

MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM)

2022 27th Asia Pacific Conference on Communications (APCC)

Sensors

Priority-based logistics and the polarization of drones in civil aviation will cause an extraordi... more Priority-based logistics and the polarization of drones in civil aviation will cause an extraordinary disturbance in the ecosystem of future airborne intelligent transportation networks. A dynamic invention needs dynamic sophistication for sustainability and security to prevent abusive use. Trustworthy and dependable designs can provide accurate risk assessment of autonomous aerial vehicles. Using deep neural networks and related technologies, this study proposes an artificial intelligence (AI) collaborative surveillance strategy for identifying, verifying, validating, and responding to malicious use of drones in a drone transportation network. The dataset for simulation consists of 3600 samples of 9 distinct conveyed objects and 7200 samples of the visioDECT dataset obtained from 6 different drone types flown under 3 different climatic circumstances (evening, cloudy, and sunny) at different locations, altitudes, and distance. The ALIEN model clearly demonstrates high rationality ac...

2022 13th International Conference on Information and Communication Technology Convergence (ICTC)

Advances in systems analysis, software engineering, and high performance computing book series, Jul 12, 2024

Drones, Feb 15, 2022

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Accurate detection of distant drones in clustered environment amidst other flying objects such as... more Accurate detection of distant drones in clustered environment amidst other flying objects such as birds is of critical importance in anti-drone system design. This study proposed a novel object detection model that efficiently detect and differentiate drones from other flying objects under different weather conditions. The custom dataset consists of manually generated drone images and bird samples under sunny, cloudy and evening conditions. The simulation result shows that KITYOLO outperformed YOLOv5 both in precision (sunny 96.2% vs 85%; cloudy 73.7% vs 26.3%; evening 58.5% vs 26.1%) and recall (evening 42.4% vs 15%) in all aspects with an overall F1-score of 98% as against 91.9% while maintaining timeliness and memory usage.

2022 International Conference on Information Networking (ICOIN), Jan 12, 2022

The surging proliferation in the deployment of unmanned aerial vehicles (UAVs) in various domains... more The surging proliferation in the deployment of unmanned aerial vehicles (UAVs) in various domains has resulted into unsolicited intrusion into private properties and protected areas thereby posing threat to national security. This paper proposed an adaptive scenario-based approach for detecting drone invasion using enhanced YOLOv5 deep learning model to detect different drones and identify attached objects operating under any environment, size, speed, or shape. The dataset consists of 6 drone models and 8 attached weapons manually generated and preprocessed to form samples. In terms of accuracy, sensitivity, and timeliness, the result shows that our model achieved superior detection precision of 100%, sensitivity of 99.9%, F1-score of 87.2% for weapons identification at a shorter time of 0. 021s than other models. The high detection accuracy undoubtedly makes our model well suited for real-time drone monitoring and countering of illegal drones in military offensives with minimal resource usage.

IEEE Access, 2022

The future of healthcare relies heavily on the connection of humans to intelligent devices via co... more The future of healthcare relies heavily on the connection of humans to intelligent devices via communication networks for rapid medical response. Hence, the evaluation of the performance of smart wearable devices as veritable tools for prompt, pervasive, and proactive healthcare delivery to end-users in response to socioeconomic dynamics is imperative especially as 5G unwinds and B5G emerges. Despite the boom in the wearable market and significant improvement in communication technologies, the translation of wearable data from clinical trials to valuable assets for practical medical application is burdened with varying challenges. This review provides an introspective analysis of the performance of unobtrusive wearable devices based on identified key performance indicators (KPIs) in relation to evolving generation networks in achieving innovative health care delivery. A total of 2751 articles pooled from 5 digital libraries were screened and 16 were selected for this review using PRISMA. The identified E-DISC wearable KPIs; energy efficiency, discretization, intelligence, secured network, and customizable standards are currently engrossed with both reliability and real-time issues that undermine its performance, perceptibility, and acceptability by end-users. The transformation of smart wearable devices' data from clinical trials into intangible resources for medical application is the fulcrum of innovative healthcare actualization. Further insight on how the identified challenges can be streamlined for smooth device alignment and transition to the emerging B5G network and its eco-friendly environment is also discussed. It is hoped that this will serve as a rallying point for research direction in translating prospective wearable solutions into a valuable resource for actualizing p-health.

Journal of intelligence, conflict and warfare, May 31, 2023

The development of a comprehensive and decisive drone defense integrated control system that can ... more The development of a comprehensive and decisive drone defense integrated control system that can provide maximum security is crucial for maintaining territorial integrity and accelerating smart aerial mobility to sustain the emerging drone transportation system (DTS) for priority-based logistics and mobile communication. This study explores recent developments in the design of robust drone defense control (D D S) systems that can observe and respond not only to drone attacks inside and outside a facility but also to equipment data such as CCTV security control on the ground and security sensors in the facility immediately. Also, it considered DDS strategies, schema, and innovative security setups in different countries. Finally, open research issues in DDS designs are discussed, and useful recommendations are provided. Effective means for drone source authentication, delivery package verification, operator authorization, and dynamic scenario specific engagement are solicited for comprehensive DDS design for maximum security.

The Domain Name System (DNS) is the hub of the cyberspace and communications services which also ... more The Domain Name System (DNS) is the hub of the cyberspace and communications services which also plays enabling role in the Industrial Internet of Things (IIoT) and transmission at large. DNS enciphering in HyperText Transfer Protocol Secure (HTTPS) as DoH did not eliminate vulnerability and intrusion into critical systems. This study proposed a time-efficient Ensemble Learning (EL) model for countering DNS vulnerability to attack. The proposed EL candidate incorporates feature selection capability in extracting relevant features for enhanced model optimization. The simulation results showed that the proposed EL candidate effectively mitigates vulnera-bility, classifying DNS traffic into Non-DoH, Malicious DoH and Benign-DoH. The proposed model outperforms other compared state-of-art EL techniques with a combined advantage of accuracy and training time of 99.5% and 13.96s.

IEEE Internet of Things Journal, Aug 15, 2023

Sensors, Jan 20, 2023

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)

2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)

The Journal of Intelligence, Conflict, and Warfare

The development of a comprehensive and decisive drone defense integrated control system that can ... more The development of a comprehensive and decisive drone defense integrated control system that can provide maximum security is crucial for maintaining territorial integrity and accelerating smart aerial mobility to sustain the emerging drone transportation system (DTS) for priority-based logistics and mobile communication. This study explores recent developments in the design of robust drone defense control systems that can observe and respond not only to drone attacks inside and outside a facility but also to equipment data such as CCTV security control on the ground and security sensors in the facility at a glance. Also, it considered DDS strategies, schema, and innovative security setups in different regions. Finally, open research issues in DDs designs are discussed, and useful recommendations are provided. Effective means for drone source authentication, delivery package verification, operator authorization, and dynamic scenario-specific engagement are solicited for comprehensive...

IEEE Internet of Things Journal

MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM)

2022 27th Asia Pacific Conference on Communications (APCC)

Sensors

Priority-based logistics and the polarization of drones in civil aviation will cause an extraordi... more Priority-based logistics and the polarization of drones in civil aviation will cause an extraordinary disturbance in the ecosystem of future airborne intelligent transportation networks. A dynamic invention needs dynamic sophistication for sustainability and security to prevent abusive use. Trustworthy and dependable designs can provide accurate risk assessment of autonomous aerial vehicles. Using deep neural networks and related technologies, this study proposes an artificial intelligence (AI) collaborative surveillance strategy for identifying, verifying, validating, and responding to malicious use of drones in a drone transportation network. The dataset for simulation consists of 3600 samples of 9 distinct conveyed objects and 7200 samples of the visioDECT dataset obtained from 6 different drone types flown under 3 different climatic circumstances (evening, cloudy, and sunny) at different locations, altitudes, and distance. The ALIEN model clearly demonstrates high rationality ac...

2022 13th International Conference on Information and Communication Technology Convergence (ICTC)