Abstract
In fish farms a major issue is the net cage wear, resulting in fish escapes and negative impact of fish quality, due to holes and biofouling of the nets. To minimize fish losses, fisheries utilize divers to inspect net cages on a weekly basis. Aquaculture companies are looking for ways to maximize profit and reduce maintenance costs is one of them. Kefalonia Fisheries spend 250 thousand euros yearly on diver expenses for net cages maintenance. This work is about the design, fabrication, and control of an inexpensive autonomous underwater vehicle intended for inspection in net cages at Kefalonia Fisheries S.A. in Greece. Its main body is 3D-printed, and its eight-thruster configuration grants it six degrees of freedom. The main objective of the vehicle is to limit maintenance costs by increasing inspection frequency. The design, fabrication as well as the electronics and software architecture of the vehicle are presented. In addition, the forces affecting Kalypso, mobility realization, navigation, and modeling are quoted along with a flow simulation and the experimental results. The proposed design is adaptable and durable while remaining cost effective, and it can be used for both manual and automatic operations.

Abstract
Getting students motivated and interested in their education can be challenging in any classroom setting, even more so in an online learning environment. In this spectrum, educational robotics (ER) has demonstrated numerous advantages in the educational environment, not only by facilitating teaching, but also enabling the cultivation of manyfold skills, including creativity, problem-solving, and teamwork. Meanwhile, many methods have been developed with the aid of technology to improve the teaching process and boost students' ability to learn. Blended learning is one approach that integrates conventional classroom methods with digital resources in an effort to foster students' creativity. But how can blended learning be combined with robotics? The objective of this paper is to evaluate the impact of employing an underwater vehicle, called educational underwater vehicle (EDUV), in conjunction with a dedicated programming learning platform within the context of a programming course that is offered at the high school level. In this work, this platform is utilized by students in secondary education, and a survey was conducted prior and after using the underwater vehicle's platform based on two questionnaires. The survey included 112 Greek participants, 64 males and 48 females in the age range of 14–18 years old. The experimental results show an increase in their motivation and creativity. In other words, they are more engaged in the classroom and the lesson becomes more enjoyable. More specifically, the survey revealed that most participants are familiar with computers but have limited knowledge of robotics and programming. After training on the EDUV platform, participants showed a significant increase in correct responses for Python and Blockly environments, with an average of 50.7% in four programming-related questions. The platform also reduced “do not know” replies, which means that the student's self-esteem increased. The paired sample T-test showed that the EDUV platform positively influenced participants' perceptions of robotics and motivated them to further their education. In this paper, the related work is discussed, and the architecture of the vehicle is analyzed, along with the integration with the online platform. In addition, the methodology performed is explained and divided into steps. Finally, the experimental results are discussed. Instructions, 3D models, and code can be found in the github repository https://github.com/MariosVasileiou/EDUV.

Abstract
In the face of increasing agricultural demands and environmental concerns, the effective management of weeds presents a pressing challenge in modern agriculture. Weeds not only compete with crops for resources but also pose threats to food safety and agricultural sustainability through the indiscriminate use of herbicides, which can lead to environmental contamination and herbicide-resistant weed populations. Artificial Intelligence (AI) has ushered in a paradigm shift in agriculture, particularly in the domain of weed management. AI's utilization in this domain extends beyond mere innovation, offering precise and eco-friendly solutions for the identification and control of weeds, thereby addressing critical agricultural challenges. This article aims to examine the application of AI in weed management in the context of weed detection and the increasing impact of deep learning techniques in the agricultural sector. Through an assessment of research articles, this study identifies critical factors influencing the adoption and implementation of AI in weed management. These criteria encompass factors of AI adoption (food safety, increased effectiveness, and eco-friendliness through herbicides reduction), AI implementation factors (capture technology, training datasets, AI models, and outcomes and accuracy), ancillary technologies (IoT, UAV, field robots, and herbicides), and the related impact of AI methods adoption (economic, social, technological, and environmental). Of the 5821 documents found, 99 full-text articles were assessed, and 68 were included in this study. The review highlights AI's role in enhancing food safety by reducing herbicide residues, increasing effectiveness in weed control strategies, and promoting eco-friendliness through judicious herbicide use. It underscores the importance of capture technology, training datasets, AI models, and accuracy metrics in AI implementation, emphasizing their synergy in revolutionizing weed management practices. Ancillary technologies, such as IoT, UAVs, field robots, and AI-enhanced herbicides, complement AI's capabilities, offering holistic and data-driven approaches to weed control. Additionally, the adoption of AI methods influences economic, social, technological, and environmental dimensions of agriculture. Last but not least, digital literacy emerges as a crucial enabler, empowering stakeholders to navigate AI technologies effectively and contribute to the sustainable transformation of weed management practices in agriculture.

Abstract
This paper introduces the El Greco Platform, a Python programming platform for distance learning that employs an educational robot. This website allows prospective learners to remotely control El Greco, a social humanoid robot designed to be cost-effective, simple to construct, and appropriate for use in education. El Greco is capable of performing multiple tasks, including combined movements. These Robot capabilities can be programmed using either Python code or the Blockly library, which adds an editor to an application that visualizes coding concepts as interlocking blocks. Programming a robot appears to be a significantly more effective and creative method for students to learn a programming language. This educational tool was designed primarily for use by students and allows anyone to learn Python while controlling a robot for free. El Greco Platform features gamification elements that increase the enjoyment and engagement of the learning experience while reinforcing the concepts taught. The survey results on students aged 13–18 revealed that the El Greco Platform captivated the study participants and positively affected their attitudes toward programming and robotics. In addition, it significantly impacted their comprehension of programming and motivated them to seek additional opportunities to expand their knowledge of robotics and programming.

Abstract
Underwater vehicles utilized in net cages at aquaculture facilities are commonly utilized for the purpose of examining the deterioration of nets and the accumulation of biofouling. The implementation of a robotic system for repairing damages has the potential to decrease the expenses associated with employing divers while reducing the risk of their injury. This study details the development, fabrication, and simulation of a cost-effective subaquatic manipulator, denoted as MURA, which can be seamlessly incorporated into submersible vehicles. The Kalypso unmanned underwater vehicle (UUV) is utilized in this study. MURA exhibits a high degree of modularity, enabling seamless alteration of the end-effector tool. Additionally, its low-cost nature renders it a viable option for integration with any underwater vehicle. Three end-effectors were subjected to testing, one designed for the purpose of disposing fish morts, another intended for removing litters from net cages in fisheries, and a third for repairing net tears. This study outlines the MURA design, including the arm’s fabrication and constituent components. In addition, the modeling of the manipulator is presented accompanied by a water flow simulation of the three manipulators. Ultimately, the experimental findings are analyzed and evaluated. These include the field experiments performed at Kefalonia fisheries, along with the duration to complete each task. For instance, the capture of fish morts typically necessitates approximately 30 s, encompassing the entire process from initial targeting to actual capture. In a similar vein, the procedure of mending tears in a net necessitates an approximate duration of 70 s on average, encompassing the stages of initial identification and subsequent detachment. The suggested design exhibits adaptability and durability while upholding affordability when utilized in aquaculture.

Abstract
Food fraud poses a significant challenge within the global food supply chain, with apprehensions regarding safety, authenticity, and efficiency. This study conducts a brief review of the literature by utilizing the Web of Science database, analyzing 2331 outcomes pertaining to the subject of food fraud. The analysis results demonstrated a noteworthy surge in scientific publications after 2013, which was propelled by events such as the horsemeat scandal and the formation of the European Food Safety Authority. Utilizing Multiple Correspondence Analysis (MCA), the study identified significant clusters pertaining to food transformation, safety, traceability, and distinct meat sources. In addition, trending topics shifted towards a holistic approach to food safety and the implementation of technologies like Blockchain (BC), Internet of Things (IoT), Artificial Intelligence (AI), and Big Data (BD). These technologies offer enhanced traceability, authentication, automation, and decision-making capabilities. The present research offers valuable perspectives on the evolving landscape of food fraud research and the potential of nascent technologies to tackle these issues.

Abstract
Conventional agricultural techniques cannot fulfill the requirements of a sustainable food value chain. Agroecology can be a great alternative practice for transforming the current agricultural systems. This approach combines ecology and agriculture, considering different stakeholders’ opinions. An assessment of the current literature about “agroecology practices” using the Web of Science database was made, and 1235 results were collected and unified into a bibtex file using R studio. The final results were extracted through the bibliometix library. The acquired results show that annual scientific production on the aforementioned term was limited between the 1990s and 2010s and has recently increased due to increased interest in the topic. Additionally, the terms “agriculture”, “management biodiversity”, and “conservation” are frequently correlated with agroecology, covering all three dimensions of sustainability. Agroecology as a trending topic has great potential to serve North African countries, increasing food security levels while assuring sustainability standards.

Abstract
In this paper, the software of Kalypso, an underwater robot designed for fisheries is presented. The software that controls the robot's movements and data processing is a critical component of its operation, and this paper provides a detailed analysis of the algorithms used to ensure reliable performance. The results of this analysis provide valuable insights for researchers and engineers working to improve the efficiency and effectiveness of underwater robots in the context of fisheries management.

Abstract
Underwater vehicles can play an essential role in fish farming and their construction can be a challenging aspect of their development owing to the necessity of waterproofing electronic components. This paper describes the construction and basic framework of a robotic vehicle named "Kalypso," which was developed to inspect nets in fish farms. Kalypso can distinguish between clean areas on the net and areas that are either torn or covered in algae, based on an algorithm. Also, it is equipped with sensors to estimate position, depth, temperature and leakage, which can detect water in the watertight housing. The watertight part of the robot includes cable plugs, some of which are detachable to facilitate the connection of various devices, such as sensors and lights. Kalypso has two cameras, one facing the front and another facing the bottom. Furthermore, the robot has underwater ultrasonic sensors, which measure the distance from the environment, and LED lights on the front for increased visibility in low-light environments. Several tests were carried out, both inside fish farm nets and in the open sea.

Abstract
A significant challenge in fish farms is net cage deterioration, which leads to fish escapes owing to holes and can have a severe influence on the fish's health due to biofouling. To reduce fish losses, divers are utilized on a weekly basis by fisheries to carry out the task of inspecting the net cages. Companies that are involved in aquaculture are always seeking for methods to increase their profits, and one of those ways is to cut down on the costs of maintenance. This paper is about the development of an unmanned underwater vehicle used for inspection in net cages at Kefalonia Fisheries in Greece. This vehicle has a 3D-printed body and a six-thruster configuration, featuring five degrees of freedom. The vehicle's primary goal is to reduce divers’ expenses by conducting inspections more frequently. In this work, the design, manufacture, and control are presented along with the experimental results and flow simulation of the vehicle. The suggested design is versatile and robust while yet being affordable, and the fisheries may easily adopt it due to its inexpensive price and simplicity of operation.

Abstract
Educational robotics is rooted in Constructionism and allows learners to investigate and discover new concepts. It would appear that learning a programming language while programming a robot is more motivating and productive than conventional methods. El Greco platform is an educational platform built to teach Python. Users can control El Greco from any computer connected to the Internet due to the platform’s web-based interface. El Greco is a social humanoid robot built to be affordable and appropriate for use in education. Potential users can use Python direct code entry or the Blockly library to control El Greco. The Blockly library embeds an editor in an application to represent coding notions like interlocking blocks. Unique functions that control El Greco were created. The inserted code can be executed on the website or by the Robot. The user can view the result of code execution through a live-streaming window. The El Greco platform has been designed with students in mind but is available to anyone at no cost.

Abstract
Remotely Operated Underwater Vehicles (ROVs) used in net cages at fish farms are usually employed to inspect net wear and biofouling. Implementing a robotic system to repair the damages can reduce diver costs and can be lucrative for the aquaculture company. This paper presents the design, fabrication, and modeling of an affordable subsea robotic arm called IURA, that can be integrated to any underwater vehicle. For this study Kalypso ROV was used. Although IURA is at its infancy, it features (i) high modularity allowing to change end-effector tool effortlessly, and (ii) lowcost which makes it feasible for any ROV integration. It is mostly 3D-printed and has two servo motors as joints featuring 2 Degrees of Freedom (DoF). Two manipulators were tested, one to dispose fish morts, and another to remove objects from the net cages at fish farms. In this work, the design of IURA will be presented along with the fabrication and sealing of the arm. Furthermore, the modeling of the robotic arm will be quoted and flow simulation of both end-effectors. Finally, the experimental results will be discussed. The proposed design features customizability and sturdiness while retaining low-cost and can be used for subsea operations at Kefalonia Fisheries’ net cages when mounted on Kalypso ROV.

Abstract
This paper introduces the conception, design, fabrication, and control of a modular remotely operated underwater vehicle. It is an affordable submarine robot intended for inspection operations in shallow depths. It has a 3D-Printed hull, and it can be adjusted according to the respective needs. It is equipped with six thrusters which allow it to have five Degrees of Freedom enabling increased maneuverability while it operates. The robot has marginally positive buoyancy which allows it to emerge in case of a malfunction, and the fins attached to the motors enhance its stability. The design, development, and construction as well as the components and electronics of the vehicle are presented. Moreover, the forces acting on the ROV and the buoyancy are introduced, along with the motion generation of the motors. The IMU sensor calibration is explained and a dataset of the rotational movement was analyzed into 3 axes. The proposed design features low cost, customizability and sturdiness allowing the user to configure and operate by himself.