John G Breslin

John G Breslin
University of Galway | NUI Galway

About

465
Publications
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8,759
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Publications

Publications (465)
Article
Full-text available
Peer-to-peer (P2P) energy trading is one of the most effective methods to increase the usage of Renewable Energy (RE) resources in the distribution network and reduce losses by eliminating long transmission and distribution lines. This research aims to enhance the efficiency of P2P energy trading by examining the suitability of four distinct double...
Article
Full-text available
Systems for monitoring air quality are essential for reducing the negative consequences of air pollution, but creating real-time systems encounters several challenges. The accuracy and effectiveness of these systems can be greatly improved by integrating federated learning and multi-access edge computing (MEC) technology. This paper critically revi...
Article
Full-text available
The Internet of Things (IoT) based smart city applications are the latest technology-driven solutions designed to collect and analyze data to enhance the quality of life for urban residents by creating more sustainable, efficient, and connected communities. Communication nodes are networked independently to monitor the circumstances, where they req...
Article
Full-text available
Industry 4.0 (I4.0) is a new era in the industrial revolution that emphasizes machine connectivity, automation, and data analytics. The I4.0 pillars such as autonomous robots, cloud computing, horizontal and vertical system integration, and the industrial internet of things have increased the performance and efficiency of production lines in the ma...
Article
Full-text available
The electric vehicles (EVs) charging stations (CSs) at public premises have higher installation and power consumption costs. The potential benefits of public CSs rely on their efficient utilization. However, the conventional charging methods obligate a long waiting time and thereby deteriorate their efficiency with low utilization. This paper sugge...
Article
Full-text available
Meaningful feature extraction from multivariate time-series data is still challenging since it takes into account the correlation between pairs of sensors as well as the temporal information of each time-series. Meanwhile, the huge industrial system has evolved into a data-rich environment, resulting in the rapid development and deployment of deep...
Chapter
The current challenging issue in the Advanced Metering Infrastructure (AMI) of the Smart Grid (SG) network is how to classify and identify smart meters under the effect of falsification attacks related to stealthy data, which are injected in such small numbers or percentages that it becomes hard to identify. The problem becomes challenging due to s...
Chapter
At least one-third of the food produced for human consumption is lost and wasted due to inefficient perishable product distribution plans. Currently used distribution plans are static and centralised as a single entity decides on a distribution plan where products may move along a predefined path. In this paper, we developed a dynamic distribution...
Chapter
Payment channel networks (PCN) are one of the promising second layer solutions for the scalability issue of cryptocurrencies. They offer high throughput and low-cost transactions for the users. However, practical and design issues of PCN hinder users from embracing the technology. This paper focuses on how to increase user adoption by boosting reve...
Chapter
Although it is difficult to overwrite the data kept in blockchains, there are numerous incidents of false data insertion in blockchains. Current blockchain technologies can not prevent such false insertion into blockchains. In this paper, we present a blockchain model that can prevent such immutable lies. We have several contributions in this paper...
Chapter
Blockchain is a promising tool to implement peer-to-peer energy trade algorithms because it lowers the cost of electricity by eliminating 3rd parties such as the utility companies from energy trade and by creating a secure trade platform. However, the state of the art blockchain-based peer to peer energy trade solutions have privacy and scalability...
Article
Full-text available
The ongoing industrial revolution termed Industry 4.0 (I4.0) has borne witness to a series of profound changes towards increasing smart automation, particularly in the industrial sectors of automotive, aerospace, manufacturing, etc. Automatic welding, a widely applied manufacturing process in these domains, is not an exception of these changes. One...
Article
With the advent of Industry 4.0 (I4.0) leading to the proliferation of industrial process data, deep learning (DL) techniques have become instrumental in developing intelligent fault diagnosis (FD) applications. However, de- spite their potentially superior process monitoring capa- bilities, DL-based FD models are poorly calibrated and generate poi...
Article
Full-text available
In recent years Cyber-Physical Systems (CPS) and Industrial Internet of Things (IIoT) have gained significant attraction; however, it remains a vulnerable target for cyberattacks. Machine learning techniques have garnered interest in security applications due to their rapid processing capabilities and real-time predictions. However, imbalanced data...
Article
Full-text available
5G emerges as the bedrock for the Industrial Internet of Things (IIoT), it facilitates the seamless, low-latency fusion of artificial intelligence and cloud computing, thereby fortifying the entire industrial procedure within a framework of smart and intelligent IIoT ecosystems. Concurrently, the continuously changing landscape of cybersecurity thr...
Article
Full-text available
The emergence of Industry 4.0 (I4.0) has transformed modern-day factories into expansive industrial sites through rapid automation and increased access to real-time data. Deep learning (DL) approaches possessing superior capabilities for intelligent data-driven fault diagnosis (FD) have become critical in ensuring process safety and reliability in...
Chapter
Smart Factories characterize as context-rich, fast-changing environments where heterogeneous hardware appliances are found beside of also heterogeneous software components deployed in (or directly interfacing with) IoT devices, as well as in on-premise mainframes, and on the Cloud. This inherent heterogeneity poses major challenges particularly whe...
Conference Paper
Full-text available
TinyML: Tiny in size, big in impact! In this paper, we present a Tensor Memory Mapping (TMM) method, which can accurately calculate the on-device execution memory consumed by a range of ML and TinyML models during execution on small central processing units (CPUs), microcontroller units (MCUs), and single board computers (SBCs).
Chapter
Full-text available
Motivation. Industry 4.0 [1, 2] comes with unprecedented amounts of heterogeneous industrial data [3,4,5].
Conference Paper
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Traditionally, original equipment manufacturers (OEMs) send device-specific over-the-air (OTA) packages to ensure the latest firmware, security patches, etc. With millions of IoT devices, even a tiny percentage of OTA failures will result in tens of thousands of globally affected consumers. The state-of-the-art OTA methods are suited for high-end A...
Conference Paper
Full-text available
With the introduction of ultra-low-power machine learning (TinyML), IoT devices are becoming smarter as they are driven by ML models. However, any loss of communication at the device level can lead to a failure of the entire IoT system or misleading information transmission. Since there exist numerous heterogeneous devices within an IoT system, it...
Conference Paper
Full-text available
Invariable of the agriculture type (precision, smart, or digital), the monitoring process of factors that increase the crop yield and growth is mostly non-ML, manually structured approaches with practical pain points. In this scenario, to reduce monitoring costs and maintenance efforts, there is a requirement for low-cost semi-autonomous distribute...
Conference Paper
Full-text available
A correct reputation management system can differentiate between low-quality and high-quality data providers in an IoT data marketplace. There are challenges in designing an unbiased and secure reputation management system that can not be manipulated by wrong feedbacks or wrong aggregation of feedbacks. In this paper, we develop a decentralised rep...
Conference Paper
Payment channel networks (PCN) are one of the promising second layer solutions for the scalability issue of cryptocurrencies. They offer high throughput and low-cost transactions for the users. However, practical and design issues of PCN hinder users from embracing the technology. This paper focuses on how to increase user adoption by boosting reve...
Conference Paper
Full-text available
Due to increasing concern about climate change, the local energy market has been revolutionized with the increase in solar photovoltaic, electric vehicles, smart home appliances, and demand response. These technologies used in the residential sector provides new opportunities for Home Energy Management System (HEMS) to manage peak hours and gain in...
Conference Paper
Full-text available
Scene graph generation aims to capture the semantic elements in images by modelling objects and their relationships in a structured manner, which are essential for visual understanding and reasoning tasks including image captioning, visual question answering, multimedia event processing, visual storytelling and image retrieval. The existing scene g...
Conference Paper
Full-text available
Although it is difficult to overwrite the data kept in blockchains, there are numerous incidents of false data insertion in blockchains. Current blockchain technologies can not prevent such false insertion into blockchains. In this paper, we present a blockchain model that can prevent such immutable lies. We have several contributions in this paper...
Conference Paper
Full-text available
At least one-third of the food produced for human consumption is lost and wasted due to inefficient perishable product distribution plans. Currently used distribution plans are static and centralised as a single entity decides on a distribution plan where products may move along a predefined path. In this paper, we developed a dynamic distribution...
Conference Paper
Full-text available
Blockchain is a promising tool to implement peer-to-peer energy trade algorithms because it lowers the cost of electricity by eliminating 3rd parties such as the utility companies from energy trade and by creating a secure trade platform. However, the state of the art blockchain-based peer to peer energy trade solutions have privacy and scalability...
Conference Paper
Peer-to-Peer (P2P) energy trading, one of the new paradigms driven by decentralization, decarbonization, and digitalization of the smart grid, has become a widespread technique in recent years. Additionally, the rise of the double auction for P2P energy trading suggests better trading algorithms with unprecedented economic and technical benefits. T...
Article
Full-text available
Huge advances in peer-to-peer systems and attempts to develop the semantic web have revealed a critical issue in information systems across multiple domains: the absence of semantic interoperability. Today, businesses operating in a digital environment require increased supply-chain automation, interoperability, and data governance. While research...
Article
Full-text available
Visual understanding involves detecting objects in a scene and investigating rich semantic relationships between the objects, which is required for downstream visual reasoning tasks. Scene graph is widely used for structured scene representation, however, the performance of scene graph generation for visual reasoning is limited due to challenges po...
Article
Full-text available
This work presents a two-layer decentralized charging approach (TLDCA) based on fuzzy data fusion concerning the economic and power layers for optimizing the charging cost of residential electric vehicles (EVs). We defined the problem with the fuzzy objective function of minimizing the charging costs and presented a detailed fuzzy integer linear pr...
Chapter
Scene graph generation aims to capture the semantic elements in images by modelling objects and their relationships in a structured manner, which are essential for visual understanding and reasoning tasks including image captioning, visual question answering, multimedia event processing, visual storytelling and image retrieval. The existing scene g...
Article
Full-text available
This article presents a novel over-the-air (OTA) technique to remotely deploy tiny ML models over Internet of Things (IoT) devices and perform tasks, such as machine learning (ML) model updates, firmware reflashing, reconfiguration, or repurposing. We discuss relevant challenges for OTA ML deployment over IoT both at the scientific and engineering...
Conference Paper
In training distributed machine learning, communicating model updates among workers has always been a bottleneck. The magnitude of impact on the quality of resultant models is higher when distributed training on low hardware specification devices and in uncertain real-world IoT networks where congestion, latency, band-width issues are common. In th...
Article
Full-text available
The proliferation of sensing technologies such as sensors has resulted in vast amounts of time-series data being produced by machines in industrial plants and factories. There is much information available that can be used to predict machine breakdown and degradation in a given factory. The downtime of industrial equipment accounts for heavy losses...
Preprint
Full-text available
The majority of IoT devices like smartwatches, smart plugs, HVAC controllers, etc., are powered by hardware with a constrained specification (low memory, clock speed and processor) which is insufficient to accommodate and execute large, high-quality models. On such resource-constrained devices, manufacturers still manage to provide attractive funct...
Conference Paper
Full-text available
TinyML refers to the intersection of machine learning (ML), mathematical optimization, and tiny IoT embedded systems. In the current era of ubiquitous connectivity and pervasive data, TinyML has emerged as an effective method to continuously analyze real-world data without the resource overhead of traditional ML hardware. However, as valuable data...
Article
Full-text available
The charging loads of electric vehicles (EVs) at residential premises are controlled through a tariff system based on fixed timing. The conventional tariff system presents the herding issue, such as with many connected EVs, all of them are directed to charge during the same off-peak period, which results in overloading the power grid and high charg...
Article
Full-text available
Electric vehicles (EVs) need to be recharged at intermediate locations, such as shopping malls, restaurants, and parking lots, to meet the daily commute requirements of their users. Currently, public electric vehicle supply equipment (EVSE) serve EVs by conventional methods, which can result in long waiting time for users. This issue reduces the tr...
Chapter
Involving an intermediary between producer-consumer environments is a common practice that reduces the managerial overhead on both parties. However, this mediation has both pros and cons. For example, it can overtake the power of producers in pricing, which could cause unfair revenue distribution. We present a novel micropayment protocol called MAR...
Preprint
Full-text available
Businesses operating in a digital world require increased automation, interoperability, and data governance for supply chain activities. A substantial amount of data generated by these operations remains unused, disconnected, or latent. The purpose of this research is to demonstrate how semantic web development can leverage ontologies to optimise d...
Article
The energy sector is undergoing a paradigm shift to integrate the increasing volume of embedded renewable energy generation and create Local Energy Communities (LEC). Peer-to-Peer (P2P) energy trading is an encouraging paradigm used to increase usage of renewable energy, decrease consumers’ electricity bills, and provide revenue to prosumers. It al...
Conference Paper
Full-text available
The concept of ML model aggregation rather than data aggregation has gained much attention as it boosts prediction performance while maintaining stability and preserving privacy. In a non-ideal scenario, there are chances for a base model trained on a single device to make independent but complementary errors. To handle such cases, in this paper, w...
Conference Paper
Full-text available
Typically a Neural Networks (NN) is trained on data centers using historic datasets, then a C source file (model as a char array) of the trained model is generated and flashed on IoT devices. This standard process impedes the flexibility of billions of deployed ML-powered devices as they cannot learn unseen/fresh data patterns (static intelligence)...
Article
Full-text available
Social bots can cause social, political, and economical disruptions by spreading rumours. The state of the art methods to prevent social bots from spreading rumours are centralised and such solutions may not be ac- cepted by users who may not trust a centralised solution being biased. In this paper, we developed a decentralised method to prevent so...
Conference Paper
Full-text available
Transmitting updates of high-dimensional neural network (NN) models between client IoT devices and the central aggregating server has always been a bottleneck in collaborative learning - especially in uncertain real-world IoT networks where congestion, latency, bandwidth issues are common. In this scenario, gradient quantization is an effective way...
Article
Full-text available
Over the recent years, Industry 4.0 (I4.0) technologies such as the Industrial Internet of Things (IIoT), Artificial Intelligence (AI), and the presence of Industrial Big Data (IBD) have helped achieve intelligent Fault Detection (FD) in manufacturing. Notably, data-driven approaches in FD apply Deep Learning (DL) techniques to help generate insigh...
Chapter
Online social network users suffer from rumors and misinformation. Most of these networks are centralized and controlled by a single entity. Such centralized entities may intervene to prevent the propagation of social media content that it considers as misinformation. However, such vetting entities may be biased and may selectively prevent misinfor...
Chapter
Full-text available
Edge analytics refers to the application of data analytics and Machine Learning (ML) algorithms on IoT devices. The concept of edge analytics is gaining popularity due to its ability to perform AI-based analytics at the device level, enabling autonomous decision-making, without depending on the cloud. However, the majority of Internet of Things (Io...
Conference Paper
Full-text available
Edge analytics refers to the application of data analytics and Machine Learning (ML) algorithms on IoT devices. The concept of edge analytics is gaining popularity due to its ability to perform AI-based ana-lytics at the device level, enabling autonomous decision-making, without depending on the cloud. However, the majority of Internet of Things (I...
Conference Paper
Full-text available
With the introduction of ultra-low-power machine learning (TinyML), IoT devices are becoming smarter as they are driven by Machine Learning (ML) models. However, any increase in the training data results in a linear increase in the space complexity of the ML models. It is highly challenging to deploy such ML models on IoT devices with limited memor...
Poster
Full-text available
Monitoring and analyzing air quality is of primary importance to encourage more sustainable lifestyles and plan corrective actions. This paper presents the design and end-to-end implementation of a real-world urban air quality data collection and analytics use case which is a part of the TRAFAIR (Understanding Traffic Flows to Improve Air Quality)...
Article
Full-text available
The development of the Internet of Things (IoT) technology and their integration in smart cities have changed the way we work and live, and enriched our society. However, IoT technologies present several challenges such as increases in energy consumption, and produces toxic pollution as well as E-waste in smart cities. Smart city applications must...
Article
The majority of IoT edge devices are embedded systems with a tiny microcontroller unit (MCU), which acts as its brain. When users want their edge devices to continuously improve for better edge-analytics results, there is a need to equip their devices with algorithms that can learn/train from the continuously evolving real-world data. Currently, su...
Conference Paper
Traditional grid network has played a major role in society by distributing and transmitting electric supply to consumers. However, with the advancement in technology in Industry 4.0 has evolved the role of the Smart Grid (SG) network. SG network is a two-way bi-directional communication Cyber-Physical System (CPS). Whereas traditional grid network...
Conference Paper
Involving an intermediary between producer-consumer environments is a common practice that reduces the managerial overhead on both parties. However, this mediation has both pros and cons. For example, it can overtake the power of producers in pricing, which could cause unfair revenue distribution. We present a novel micropayment protocol called MAR...
Article
Full-text available
The healthcare Internet-of-Things (IoT) offers many benefits including data transmission in real-time mode, the ability to monitor the physiological state of the patient in a different interval of time. Devices such as blood-pressure monitors, glucose meters, heart monitoring implants, Electroencephalography (EEG), Electrocardiogram (ECG), and Elec...
Conference Paper
Full-text available
By increasing energy trading in a microgrid, we can reduce the energy burden of the main grid, generate surplus power, reduce transmission and distribution losses, and save electricity bill. One of the options for curbing surplus energy flow, which will help maintain a dynamic equilibrium in the power grid between supply and demand, is Peer to Peer...
Conference Paper
Full-text available
The advancement in renewable energy sources (RESs) technology have changed the role of traditional consumers to prosumers. In contrast to the traditional power grid, the Smart Grid (SG) network provides a platform for peer-to-peer (P2P) energy trading between prosumers to buy or sell energy according to their requirements. The potential benefits of...
Article
Full-text available
In recent years, due to technological advancements, the concept of Industry 4.0 (I4.0) is gaining popularity, while presenting several technical challenges being tackled by both the industrial and academic research communities. Semantic Web including Knowledge Graphs is a promising technology that can play a significant role in realizing I4.0 imple...
Conference Paper
Full-text available
With the introduction of edge analytics, IoT devices are becoming smarter and ready for AI applications. However, any increase in the training data results in a linear increase in the space complexity of the trained Machine Learning (ML) models, which means they cannot be deployed on IoT devices that have limited memory. To alleviate such memory is...