Dimitrios Tzovaras

The Centre for Research and Technology, Hellas · Information Technologies Institute (ITI)

The industrial revolution 4.0 has led to a burst in the development of robotic automation and platforms to increase productivity in the industrial and health domains. Hence, there is a necessity for the design and production of smart and multi-functional tools, which combine several cutting-edge technologies, including additive manufacturing and sm...

Ultraviolet (UV) radiation is part of the optical spectrum of the solar light. Exposure to ultraviolet radiation for prolonged periods of time can cause damage to skin cells and lead to the development of both non-melanoma cancer and melanomas. Workers in constructions sites are particularly susceptible to exposure in UV radiation due to the prolon...

This paper presents a comprehensive review of ground agricultural robotic systems and applications with special focus on harvesting that span research and commercial products and results, as well as their enabling technologies. The majority of literature concerns the development of crop detection, field navigation via vision and their related chall...

IoT has a profound impact on businesses and individuals as its adoption grows. Security and scalability are key subjects for enabling the technology's adoption. Cyber attacks increase each year, and the addition of emerging technologies such as Machine Learning can introduce vulnerabilities with additional complexity. Access control can mitigate se...

Recent advances in additive manufacturing (AM) led to the design and production of geometrical complex items with a plethora of materials facilitating the implementation of topology optimization procedures. Lattice designs are often employed for the topology optimization process providing lightweight structures with also additional advantages, such...

Throughout history, people have migrated from one place to another. People try to reach European shores for different reasons and through different channels. The “European migration crisis” is still ongoing and more than 34,000 migrants and refugees have died trying to get to Europe since 1993. Migrants look for legal ways, but also risk their live...

Partner Notification (PN) processes are typically part of wider combination prevention efforts and focus on the notification of sexual partners to prevent Sexually Transmitted Infections (STIs), including Human Immunodeficiency Viruses and viral hepatitis. We present a free, voluntary, anonymous and GDPR-compliant Partner Notification service that...

Behavioral monitoring tools can be proven to be especially helpful for aging workers for whom it is of paramount importance to avoid sedentary lifestyle, decreasing the possibility to exhibit musculoskeletal, cardiovascular and other health/mental related problems, which could impede their workability and job performance. Towards this direction, we...

Aiming to address the needs of the ageing workforce in the context of shift work, we introduce a Participatory Work Orchestration Support Tool, with the aim of supporting decision making in deriving the periodic shift schedule of an organization. The proposed tool comprises two main components, an extensive and intuitive web-based platform that ena...

Modern augmented and virtual reality (AR/VR) technology open multiple new capabilities in the way people interact, collaborate and deliver or receive information via digital interfaces. Industry workers and operators may especially benefit from such solutions that allow them to get trained, onsite or remotely, using digital copies of the workplace...

Anomaly detection is concerned with identifying rare events/observations that differ substantially from the majority of the data. It is considered an important task in the energy sector to enable the identification of non-standard device conditions. The use of anomaly detection techniques in small-scale residential and industrial settings can provi...

The transition from traditional dispatchable generation units to intermittent supply from renewable energy sources, as well as the continuous rise in energy demand, partially due to the growing popularity of electric vehicles (EVs), has sparked an upsurge in research interest for energy related forecasting in recent decades. The heavy reliance on w...

The COVID-19 pandemic has created significant restrictions to passenger mobility through public transportation. Several proximity rules have been applied to ensure sufficient distance between passengers and mitigate contamination. In conventional transportation, abiding by the rules can be ensured by the driver of the vehicle. However, this is not...

Diagnosing abnormal behavior of different severity and convenience effects in a real-time manner is of paramount importance for energy-intensive building appliances. Both industrial and residential sectors suffer from post-incident maintenance where undetected faults occur for several days until the total breakdown of the equipment. To generate the...

Filtering refers to the process of defining, detecting and correcting errors in a given dataset, to achieve system reliability and minimize the impact of errors in data analysis. Automated and accurate tools for data filtering and healing are crucial to ensure reliability of the system. This study aims to investigate statistical and machine-learnin...

Even though occupancy inference is of utmost importance for numerous real-time and real-life applications a widely-accepted approach to predict occupancy does not exist. In this paper, an assessment of widely-recommended approaches and data processing for occupancy is overviewed. Furthermore, the correlation and meta-analysis between various sensor...

Prescriptive maintenance has recently attracted a lot of scientific attention. It integrates the advantages of descriptive and predictive analytics to automate the process of detecting non nominal device functionality. Implementing such proactive measures in home or industrial settings may improve equipment dependability and minimize operational ex...

Purpose: During Minimally Invasive Surgery (MIS) procedures, there exists an ever-growing/apparent need for providing computer generated visual feedback to the surgeon(s), through a visualization device. While multiple solutions have been proposed in the literature, there is limited evidence of such a system performing reliably in practice, and wh...

Background: Major chronic diseases such as cardiovascular disease (CVD), diabetes, and cancer impose a significant burden on people and health care systems around the globe. Recently, deep learning (DL) has shown great potential for the development of intelligent mobile health (mHealth) interventions for chronic diseases that could revolutionize th...

THe energy-efficient operation of microgrids—a localized grouping of consuming loads (domestic appliances, EVs, etc.) with distributed energy sources such as solar photovoltaic panels—suggests the deployment of Energy Management Systems (EMSs) that enable the actuation of controllable microgrid loads coupled with Artificial Intelligence (AI) tools....

Non-intrusive load monitoring (NILM), or else energy disaggregation, aims at decomposing the aggregated energy consumption data, estimating the contribution of each appliance to the total building energy consumption. The current paper introduces a supervised algorithm for the accurate estimation of both power consumption and operational state of th...

Home Energy Management Systems (HEMSs) are developed to facilitate residential energy management towards a more efficient way while enhancing the residents' energy awareness. Within this paper, a novel non-intrusive, advisory and low-cost home eNeRGy management system FOR a Unique load profile (NRG4-U) is proposed to generate a target personalized...

Critical everyday activities handled by modern IoT Systems imply that security is of major concern both for the end-users and the industry. Securing the IoT System Architecture is commonly used to strengthen its resilience to malicious attacks. However, the security of software running on the IoT must be considered as well, since the exploitation o...

Industrial equipment/machinery is an important element of manufacturing. They are used for producing objects that people need for everyday use. Therefore, there is a challenge to adopt effective maintenance strategies to keep them well-functioning and well-maintained in production lines. This will save energy and materials and contribute genuinely...

Remanufacturing is an activity of the circular economy model whose purpose is to keep the high value of products and materials. As opposed to the currently employed linear economic model, remanufacturing targets the extension of products and reduces the unnecessary and wasteful use of resources. Remanufacturing, along with health status monitoring,...

Cybersecurity concerns have been at the forefront of regulatory reform in the European Union (EU) recently. One of the outcomes of these reforms is the introduction of certification schemes for information and communication technology (ICT) products, services and processes, as well as for data processing operations concerning personal data. These s...

During the recent years, several new Information and Communication Technology solutions have been developed in order to meet the increasing needs of elderly with cognitive impairments and support their autonomous living. Most of these solutions follow a human-centred paradigm that aims to provide users with personalised services according to their...

Software vulnerabilities constitute a critical threat for cybersecurity analysts in the contemporary society, since the successfully exploited vulnerabilities could harm any system in terms of Confidentiality, Integrity and Availability. Similarly, the characterization of vulnerabilities and the assessment of vulnerability risk is a crucial task fo...

Many seaports worldwide attempt to gain energy efficiency towards reducing their energy costs while mitigating climate change and environmental effects. In this paper , a low-cost business-oriented seaport energy effective management (PERFFECT) platform is introduced. PERFFECT intends to gain knowledge on fundamental port operational and business p...

Many seaports worldwide attempt to gain energy efficiency towards reducing their energy costs while mitigating climate change and environmental effects. In this pa- per, a low-cost business-oriented seaport energy effective management (PERFFECT) platform is introduced. PERFFECT intends to gain knowledge on fundamental port operational and business...

Selective laser melting (SLM) is one of the most reliable and efficient procedures for Metal Additive Manufacturing (AM) due to the capability to produce components with high standards in terms of dimensional accuracy, surface finish, and mechanical behavior. In the past years, the SLM process has been utilized for direct manufacturing of fully fun...

The Internet of Things (IoT) encompasses multiple fast-emerging technologies controlling and connecting millions of new devices every day in several application domains. The increased number of interconnected IoT devices, their limited computational power, and the evolving sophistication of cyber security threats, results in increased security chal...

This paper presents a critical approach to the non-intrusive load monitoring (NILM) problem, by thoroughly reviewing the experimental framework of both legacy and state-of-the-art studies. Some of the most widely used NILM datasets are presented and their characteristics, such as sampling rate and measurements availability are presented and correla...

This review article explores and locates the current state-of-the-art related to application areas from freight transportation, supply chain and logistics that focuses on arrival time, demand forecasting, industrial processes optimization, traffic flow and location prediction, the vehicle routing problem and anomaly detection on transportation data...

Fused filament fabrication (FFF) is one of the fastest-growing additive manufacturing processes due to its low operational cost and the capability to rapidly construct prototypes with complex geometrical structures. Albeit the fact that FFF technology has been widely studied, the printing conditions that offer the optimum mechanical behavior exploi...

During the last few decades, great research endeavors have been applied to healthcare robots, aiming to develop companions that extend the independent living of elderly people. To deploy such robots into the market, it is expected that certain applications should be addressed with repeatability and robustness. Such application is the assistance wit...

Background: Augmented reality (AR) and artificial intelligence (AI) are highly disruptive technologies that have revolutionised practices in a wide range of domains, including the security sector. Several law enforcement agencies (LEAs) employ AI in their daily operations for forensics and surveillance. AR is also gaining traction in security, part...

Partner Notification processes focus on the notification of sexual partners to prevent the transmission of Sexually Transmitted Infections (STIs). The INTEGRATE Joint Action provides an integrated platform called RiskRadar, for combination prevention activities targeting STIs, including an anonymous, free and voluntary Partner Notification service....

A way to improve energy management is to perform balancing both at the Peer-to-peer (P2P) level and then at the Virtual Microgrid-to-Virtual Microgrid (VMG2VMG) level, while considering the intermittency of available Renewable Energy Source (RES). This paper proposes an interdisciplinary analytics-based approach for the formation of VMGs addressing...

With the increasing amounts of electronic health data being constantly generated in medical examinations and by sensors and mobile applications, data visualization methods can assist medical professionals and researchers in exploring and making sense of the data. Two important challenges faced by data visualization are large data volume and protect...

This work presents a cognitive analytics platform for anomaly detection which is capable to handle, analyze and exploit resourcefully machine data from a shop-floor of factory, so as to support the emerging and growing needs of manufacturing industry. The introduced system contributes to industrial digitization and creation of smart factories by pr...

In the emerging era of transportation, the Internet of Vehicles envisions a large ecosystem where vehicles, traffic infrastructure, smart city sensors, and citizens will interoperate, providing safe and fast transportation services. How close are we to realizing this concept?

Current CNN-based stereo matching methods have demonstrated superior performance compared to traditional stereo matching methods. However, mapping these algorithms into embedded devices, which exhibit limited compute resources, and achieving high performance is a challenging task due to the high computational complexity of the CNN-based methods. Th...

Autonomous Vehicles (AVs) can potentially reduce the accident risk while a human is driving. They can also improve the public transportation by connecting city centers with main mass transit systems. Creating a system that can provide a sense of security to the passenger, when the driver is missing, remains a challenging task. In this work, an imag...

There is a tendency, during the last years, to migrate from the traditional homogeneous clouds and centralized provisioning of resources to heterogeneous clouds with specialized hardware governed in a distributed and autonomous manner. The CloudLightning architecture proposed recently introduced a dynamic way to provision heterogeneous cloud resour...

Energy sector stakeholders, such as Distribution System Operators (DSO) or Aggregators take advantage of improved forecasting methods. Increased forecasting accuracy facilitates handling energy imbalances between generation and consumption. It also supports Smart Grid framework processes, such as Demand-Side or Demand Response Management (DRM). Thi...

Sedentary behavior is considered as a major public health challenge, linked with many chronic diseases and premature mortality. In this paper, we propose a steps counting -based machine learning approach for the prediction of sedentary behavior. Our work focuses on analyzing historical data from multiple users of wearable physical activity trackers...

Many visual scene understanding applications, especially in visual servoing settings, may require high quality object mask predictions for the accurate undertaking of various robotic tasks. In this work we investigate a setting where separate instance labels for all objects under view are required, but the available instance segmentation methods pr...

Even though weather time series are easy to be found, complete and large data sets are almost impossible to be retrieved. In this paper, an assessment of missing weather data in small data sets is introduced utilizing correlation and meta-analysis of different weather parameters like temperature, humidity and wind speed. Auto regressive integrated...

In recent years, the growing use of Intelligent Personal Agents in different human activities and in various domains led the corresponding research to focus on the design and development of agents that are not limited to interaction with humans and execution of simple tasks. The latest research efforts have introduced Intelligent Personal Agents th...

Europe's latest energy framework aims to decrease energy consumption and mitigate carbon dioxide emissions while regulating thermal comfort for the occupants through Home energy management systems (HEMSs) or Building Management Systems (BMSs). In this paper, a practical approach for IoT interconnecting sensors and actuators to a BMS is presented. T...

Energy performance of the building stock has been identified as one of the core challenges in the effort towards improving not only energy efficiency, but also achieving zero and positive energy buildings. With the recast of the Energy Performance of Buildings Directive, Europe has made clear that improved schemes are required for more accurate ass...