Gregory O'Hare

Trinity College Dublin | TCD · School of Computer Science and Statistics

Recreational bathing waters are complex systems with diverse inputs from multiple anthropogenic and zoogenic sources of faecal contamination. Faecal contamination is a substantial threat to water quality and public health. Here we present a comprehensive strategy to estimate the contribution of faecal indicator bacteria (FIB) from different biologi...

Smart agriculture relies on accurate yield maps as a crucial tool for decision-making. Many yield maps, however, suffer from spatial errors that can compromise the quality of their data, while several approaches have been proposed to address some of these errors, detecting voids or holes in the maps remains challenging. Additionally, the quality of...

Bacteriophages have been shown to play an important role in harbouring and propagating antibiotic resistance genes (ARGs). Faecal matter contains high levels of phages, suggesting that faecal contamination of water bodies may lead to increased antimicrobial resistance (AMR) levels due to increased phage loading in aquatic environments. In this stud...

Timely data quality assessment has been shown to be crucial for the development of IoT-based applications. Different IoT applications’ varying data quality requirements pose a challenge, as each application requires a unique data quality process. This creates scalability issues as the number of applications increases, and it also has financial impl...

An understanding of water exchange processes is essential for assessing water quality management issues in coastal bays. This paper evaluates the impact of water exchange processes on pollution persistence in a macro-tidal semi-closed coastal bay through two transport time scales (TTS), namely residence and exposure times. The numerical model was c...

Novel approaches are needed to better facilitate dynamic service replication management in mobile ad-hoc networks (MANETs) and to use and apply them within current and emerging autonomous intelligent systems and the Internet of Things (IoT) paradigm. Such approaches should address the context-awareness and self-adaptation of service replication, wh...

The WHO recognises antimicrobial resistance (AMR) as a global health threat. The environment can act as a reservoir, facilitating the exchange and the physical movement of resistance. Aquatic environments are at particular risk of pollution, with large rivers subject to pollution from nearby human, industrial or agricultural activities. The land us...

Smart agriculture offers the potential to analyse agricultural data at a scale not previously possible. Researchers argue that the combination of rich data and intelligent decision support has the potential to improve productivity and profitability in agriculture, whilst also improving sustainability. We argue that achieving this potential requires...

Historical meteorological datasets are indispensable for forming climatic models and the generation of weather forecasts. Such data are core to the training phase of prediction models and may also be harnessed for hydrological and environmental models. GRIB is the most common data format used in meteorology and represents the de facto standard for...

With water quality management processes, identifying and interpreting relationships between features, such as location and weather variable tuples, and water quality variables, such as levels of bacteria, is key to gaining insights and identifying areas where interventions should be made. There is a need for a search process to identify the locatio...

Quality data is crucial to dependable, trustworthy data analytics and data-driven decision-making in IoT-based applications. Data pre-processing and data cleaning are the only considered strategies for data quality assurance. Whilst these have provided usable results, within IoT, a problem still exists. Data quality issues within IoT proliferate th...

In recent years, renewable energy, especially photovoltaic (PV) generation, has been widely applied in commercial and residential areas, forming the structure of regional microgrids (MG). On the other hand, as large-scale electric vehicles (EVs) are connected to the regional MG, their disordered charging and discharging will enable extremely bad ef...

Continued development of communication technologies has led to the widespread Internet of Things (IoT) integration into various domains, including health, manufacturing , automotive and precision agriculture. This has further led to the increased sharing of data amongst such domains to abet innovation. Most of these IoT deployments, however, are ba...

Reward shaping is an important means of reducing the computational costs associated with deep reinforcement learning in environments with sparse rewards. However, serious concerns exist over the subjectivity and self-centred motivations introduced with artificial reward design. This paper presents an objective approach to reward shaping. Reward is...

The Internet of Things (IoT) facilitates real-time decision support within smart environments. Augmented Reality (AR) allows for the ubiquitous visualization of IoT-derived data, and AR visualization will simultaneously permit the cognitive and visual binding of information to the physical object(s) to which they pertain. Essential questions exist...

The Internet of Things (IoT) provides unprecedented opportunities for the access to and conflation of a myriad of heterogeneous data to support real-time decision-making within smart environments. Augmented Reality (AR) is on cusp of becoming mainstream and will allow for the ubiquitous visualization of IoT derived data. Such visualization will sim...

Photovoltaic (PV) power is progressively being subsumed into power grids. As a consequence, reliable PV power forecasting has become essential in order to ensure the optimal functioning of the power grid. Neural networks remain the dominant prediction model utilized. Conventional neural network forecasting models are wholly dependent upon offline d...

Background: Citizen science offers an attractive paradigm for addressing some of the complex problems facing society. However, translating the paradigm’s potential into meaningful action and sustainable impact remains a formidable challenge. Historically, the citizen science landscape was fractured into silos of activities; nonetheless, it has demo...

Accurate and reliable real-time urban traffic management can benefit urban citizens’ daily life by reducing stress, travel time and carbon footprint. The provision of reliable and accurate traffic information has however proven to be a major challenge in intelligent transportation systems. Citizens carrying smartphones can be exploited as an import...

pre>The paper discusses practices and patterns for the development of maintainable and testable software using the React and Spring Boot frameworks. There have been many textbooks written on both React and Spring Boot, but little in the way of comprehensive research studies and critical analyses in the literature. The paper draws from a well-known...

pre>The paper discusses practices and patterns for the development of maintainable and testable software in relation to the development applications that use the React and Spring Boot frameworks. There have been many textbooks written on both React and Spring Boot, but little in the way of comprehensive research studies and critical analyses in the...

pre>The paper discusses practices and patterns for the development of maintainable and testable software in relation to the development applications that use the React and Spring Boot frameworks. There have been many textbooks written on both React and Spring Boot, but little in the way of comprehensive research studies and critical analyses in the...

pre>The paper discusses practices and patterns for the development of maintainable and testable software using the React and Spring Boot frameworks. There have been many textbooks written on both React and Spring Boot, but little in the way of comprehensive research studies and critical analyses in the literature. The paper draws from a well-known...

Fecal pollution of surface water may introduce bacteria and bacteriophages harboring antibiotic resistance genes (ARGs) into the aquatic environment. Watercourses discharging into the marine environment, especially close to designated bathing waters, may expose recreational users to fecal pollution and therefore may increase the likelihood that the...

Small urban streams discharging in the proximity of bathing waters may significantly contribute to the deterioration of water quality, yet their impact may be overlooked. This study focuses on the Elm Park stream in the city of Dublin that is subject to faecal contamination by unidentified sources. The aim of the study was to identify a minimum num...

Bathing water quality may be negatively impacted by diffuse pollution arising from urban and agricultural activities and wildlife, it is therefore important to be able to differentiate between biological and geographical sources of faecal pollution. crAssphage was recently described as a novel human-associated microbial source tracking marker. This...

Leaf wetness is an important input parameter into disease prediction models. The use of machine learning algorithms for the classification of leaf wetness measurements from 30 meteorological stations in North Western Europe during the period of January 2014 to October 2018 was assessed in this study. The accuracy of the empirical models utilised wi...

Growth stage determination plays an important role in yield prediction and cereal husbandry decision-making. Conventionally, crop growth stage determination is performed manually by means of visual inspection. This paper investigates wheat and barley growth stage estimation by classification of proximal images using convolutional neural networks (C...

This paper presents a survey of image processing techniques proposed in the literature for extracting key cereal crop growth metrics from high spatial resolution, typically proximal images. The descriptive crop growth metrics considered are: crop canopy cover, above ground biomass, leaf area index (including green area index), chlorophyll content,...

Engineering sustainable cyber-physical-social systems demand a transdisciplinary approach. Within an arbitrary domain, many systems, including those of the physical and cyber categories, may already be in-situ; however, heterogeneity permeates such systems, for example, differing protocols, data formats, among others. Heterogeneity is not a deliber...

Smart vehicles use sophisticated sensors to capture real-time data. Due to the weak communication capabilities of wireless sensors, these data need to upload to the cloud for processing. Sensor clouds can resolve these drawbacks. However, there is a large amount of redundant data in the sensor cloud, occupying a large amount of storage space and ne...

Varying the rate of application of agronomic inputs generates many positive economic and environmental impacts. Increasingly, technologies that enable variable rate application are becoming a distinctive feature of precision agriculture. Nonetheless, a prerequisite, and crucial challenge, remains the optimal and operational designation of distinct...

Existing research recognizes the critical role of quality data in the current big-data and Internet of Things (IoT) era. Quality data has a direct impact on model results and hence business decisions. The growth in the number of IoT-connected devices makes it hard to access data quality using traditional assessments methods. This is exacerbated by...

The Platform for Atlantic Geohazard Risk Management (AGEO) is a new project co-nanced under the Interreg Programme for the Atlantic Area which aims to launch ve Citizens' Observatory pilots on geohazards according to regional priorities: Citizens' observatory on rockfalls and rockfall-triggers in the Canary Islands, Spain Peat-slides and peat massm...

Recent developments in Internet of Things have heightened the need for data sharing across application domains to foster innovation. As most of these IoT deployments are based on heterogeneous sensor types, there is increased scope for sharing erroneous, inaccurate or inconsistent data. This in turn may lead to inaccurate models built from this dat...

Internet of Things devices and data sources are seeing increased use in various application areas. The proliferation of cheaper sensor hardware has allowed for wider scale data collection deployments. With increased numbers of deployed sensors and the use of heterogeneous sensor types there is increased scope for collecting erroneous, inaccurate or...

Activities of Daily Living systems (ADLs) and the User Interface (UI) design principles used to implement them empowers the elderly to continue living a normal daily routine. The daily monitoring of activities for most Assisted Living (AL) systems demands/necessitates accurate daily user interaction, and the design principles for these systems ofte...

Holistic information systems for climate-smart agriculture demands the seamless integration of various categories of climate, meteorological and weather data. Any actor in the agricultural value chain may harness weather forecasts at the short and medium-range, local weather history, and prevailing climatic conditions, to inform decision-making. We...

Antibiotic resistance represents the greatest challenge to healthcare systems around the world. As antibiotic resistance genes (ARGs) are shed in faeces, many studies have focused on how wastewater effluent contributes to ARG pollution in rivers. However, small urban streams and bathing waters not impacted by treated wastewater have received little...

The ever increasing proportion of photovoltaic (PV), which is, in effect, a random and intermittent energy source, makes PV power forecasting increasingly important for power grid stability. Artificial neural networks (ANN) have become one of the commonly utilized methods in PV power prediction. Since there is no ideal theoretical guidance as yet o...

This book constitutes the refereed post-conference proceedings of the 8th International Conference on Mobile Communication and Healthcare, MobiHealth 2019, held in Dublin, Ireland, in November 2019. The 26 revised full papers were reviewed and selected from 45 submissions and are organized in topical sections on mobility and real-time assessment, r...

This paper describes an agent programming language agnostic implementation of the Multi-Agent MicroServices (MAMS) model - an approach to integrating agents within microservices-based architectures. In this model, agents, deployed within microservices, expose aspects of their state as virtual resources that are externally accessible using REpresent...

Establishing food security remains a global challenge; it is thus a specific objective of the United Nations Sustainable Development Goals for 2030. Successfully delivering productive and sustainable agricultural systems worldwide will form the foundations for overcoming this challenge. Smart agriculture is often perceived as one key enabler when c...

Rough K-Means (RKM) is an efficient clustering algorithm for overlapping datasets, and has captured increasing attention in recent years. Rough k-means algorithms in the main focus on the further description of uncertain objects located in boundary regions in order to improve the performance. However, most available RKM algorithms fail to pay atten...

This paper explores the intersection between microservices and Multi-Agent Systems (MAS), introducing the notion of a new approach to building MAS known as Multi-Agent MicroServices (MAMS). Our approach is illustrated through a worked example of a Vickrey Auction implemented as a microservice.

With the rapid development of China’s economy, the scale of the city has been continuously expanding, industrial enterprises have been increasing, the discharge of multiple pollutants has reached the top of the world, and the environmental problems become more and more serious. The air pollution problem is particularly prominent. Air quality has be...

Disaster Risk Reduction (DRR) has become the predominant strategy for pre‐emptively countering the havoc threatened by natural hazards, complementing traditional disaster management and recovery activities. An important component of DRR activities is community involvement, imbuing the community with a sense of ownership of the risk reduction proces...

As the world's population ages, Ambient Assisted Living becomes a topic of considerable interest. At present, multimodal user interfaces in Ambient Assisted Living systems are an important research area. The contribution of this paper is to ascertain the needs of caregivers and family members, pertaining to the activities of daily living informatio...

Social robots are increasingly being used to encourage social, emotional and cognitive growth in children. However, in order to establish social and bonding interactions, social robots need to be able to exhibit adaptive strategies to keep children engaged and interested. Adaptive strategies of a social robot based on children’s age and gender are...

Robust activity recognition in near real-time is a prerequisite for delivering the smartness intrinsic to the pragmatic realisation of smart homes, environments and so forth. Many of the physical devices necessary for equipping a smart home are already available as consumer electronic devices and certified for use by the public. Yet activity recogn...

Europe’s social agenda for the “active elderly” is based upon a series of programs that provide a flexible infrastructure for their lives so that they are motivated, engaged in lifelong learning, and contributing to society. Economically speaking, Europe must engage in active aging research in order to avoid unsustainable health costs, and ambient...

With the growth of the Internet, crowdsourcing has become a popular way to perform intelligence tasks that hitherto would be either performed internally within an organization or not undertaken due to prohibitive costs and the lack of an appropriate communications infrastructure. In crowdsourcing systems, whereby multiple agents are not under the d...

Heterogeneity represents a singular barrier to the cross-domain adoption of sensor networks, limiting the take-up of Ambient Intelligence. Historically, the preferred approach has been to adopt a middleware solution to mitigate the problems associated with heterogeneity. Normally, the sensor discovery process is tightly coupled to the middleware pl...

Being requested several times, I think it is a good idea to put the paper's simulation (matlab) code here. Files included in this folder: Matlab script files: 1. HEED.m, heed protocol implemented by Mohammad Hossein Homaei 2. BEE.m, modified based on HEED, single hop version of the proposed protocol by Lina Xu 3. BEEM.m, modified based on HEED,...

In order to establish social and bonding relationships with children, robots need to be able to adapt to a variety of users of different age and gender groups in order to keep them engaged and motivated. To this end, this research examines the responses of 107 children, ages 5 to 12, who interacted with humanoid robot NAO that communicated with syn...

Garlic prices fluctuate dramatically in recent years and it is very difficult to predict garlic prices. The autoregressive integrated moving average (ARIMA) model is currently the most important method for predicting garlic prices. However, the ARIMA model can only predict the linear part of the garlic prices, and cannot predict its nonlinear part....

Wireless Sensor Network (WSN) systems are typically composed of thousands of sensors that are powered by limited energy resources. To extend the networks longevity, clustering techniques have been introduced to enhance energy efficiency. This paper presents a survey on clustering over the last two decades. Existing protocols are analysed from a Qua...