• COVID-19
• 2018-2022close
• WHO Global literature on coronavirus disease close
• Repositorio Digital Universidad Don Bosco close
• COVID-19 close
• Rural Digital Europe close

Telepresence and telemanipulation robotics are suitable solutions to relieve humans from direct health risks and repetitive or unhealthy work. Through demographic changes in western countries and the COVID-19 pandemic, this relief is also considered for healthcare workers, especially caregivers, as the demands for them rises. The requirements are intuitively usable telerobotic and telepresence systems for remote assistance, to cut the high physical strain in manual patient transfers and the reduction of contact with infected patients. To ensure this, key technologies like 3D imaging and perception systems are essential. In this work, we present a novel, lightweight telepresence and telemanipulation system, specialized for caregiving. It allows an operator, wearing a virtual reality headset, to immerse into a sensor system captured scene on a distant location in real-time, with low latency of 250 ms and up to 30 fps refresh rate. Extensive measurement shows that 97.1% of the relevant point cloud data is below 1 cm error and 99.5 % is below 1.6 cm, making the system suitable for the application.

This paper presents an overview of a smart city 4.0 framework in accelerating digital transformation, especially during the COVID-19 pandemic, using Jakarta as a case study. The findings of this study provide new insights how to translate a vision into a reality in the form of smart city 4.0 framework that offers a significant opportunity to advance the understanding of building a smart city ecosystem with technologies, innovations and collaborations. This paper applies four principles of the framework, namely mobile-first, system-and-data driven, digital experience, and smart collaboration in building a smart city 4.0 ecosystem platform. Part of the aim of this paper is to examine Jakarta's super-app called JAKI that is compatible with such principles as a use case in the time of the pandemic. It provides a better understanding of common elements in building a new concept of a smart city. The results will inspire and give a contribution to other cities to consider the framework in building a smart city 4.0 ecosystem platform to foster quality of life, economic growth and sustainability.

Wearable systems are promising Internet of Things (IoT) solutions that have attracted researchers’ attention in the last decade. They are getting more consideration after the COVID-19 pandemic. Information Quality (IQ) is essential for obtaining value from wearable IoT systems. In our earlier work, we proposed a complete framework that systemically developed a total IQ assessment of the IoT systems. The framework was initially validated by conducting a comparison study. Therefore, this paper aims to validate the utility of the earlier framework by using a single-case experiment. This experiment studies the use of the framework in defining IQ assessment for medical wearable IoT devices. The methodology of the experiment involves conducting literature surveys. This paper successfully uses wearable systems as a case to test the assessment processes of the IQ framework for the IoT systems. However, the case effectively indicates the importance of the framework pillars: the data quality dimensions and the IoT elements by assessing the medical wearables.

The significant decrease in agricultural land and the rapid development of hydroponic system technology have brought a huge challenge to farmers. This paper describes the NFT-I (Nutrient Film Technique based on IoT) hydroponic system, and it is a variant of traditional NFT and Floating Root (RF) systems. The system measures several parameters, such as temperature, water level, and acidity (pH). The system collects the information using sensors connected to Arduino microcontroller and Raspberry PI to store the collected data. The results show that this system can reduce the electricity consumption by 91.6%; on the other hand, it helps farmers to increase the effectivity and efficiency on monitoring and controlling NFT-I Hydroponic Farm. Finally, in these times of confinement due to coronavirus disease (COVID-19), in which the economy has decreased, and the needs are multiple, this NFT-I system could help people to create their vegetable growing system quickly and cheaply.

The advancements in Computer Vision with Deep Learning are playing an essential role in aiding Healthcare Organizations to offer better patient care while reducing costs and improving efficiencies. The medical industry has seen a sharp growth since the past few decades and it has benefited thousands of living beings. Skin being the largest part of human beings, it has never been given the proper care nor importance, hence widely resulting in the ignorance of skin infections or cancers. Despite the diagnosis of several such diseases being detected at the later or critical stages, there is a little to no scope of detection where the affected people can identify the symptoms immediately and could reach a physician. In this paper, we present the development of a model using deep learning approach to identify the specific dermatitis and a mobile application that functions in a way to detect the disease when a picture of the symptomatic part is taken and uploaded. This scheme assists the medical professionals and patients during pandamic situations like COVID 19. This application is user friendly and very much useful for the people living in rural areas and hilly area where it takes long time and expenditure to reach hospitals.

The article notes the inevitability and prospects of global digital transformation. The leading countries have already been identified. These are Korea, the United States, Great Britain, Japan, and Germany. The reasons for rapid success are the increase in the number of highly qualified and competent specialists in the field of digital technologies and, most importantly, constant public and private investment in information resources in promising areas, such as smart city projects. The priorities that smart technologies give for all stakeholders are highlighted: resource saving, high quality of services provided at an adequate price, transparency of payments, comfort and functionality of housing. The number of Russian enterprises that operate effectively in the field of information technology is very small due to the lack of permanent funding, effective domestic information infrastructure and regulatory regulation of the digital environment, and low legal and information literacy of the population. The factors influencing the development of housing and utilities and the quality of public services are summarized and systematized: organizational and managerial, scientific and technical, social, sanitary and epidemiological, environmental. The quality of housing and utilities services varies greatly from low to high across the country, due to different approaches to the organization and management of enterprises in the industry, including the information component. An overview of the latest specific IT solutions for this sphere developed in Russia is given and the necessity of creating a common digital space is emphasized, its main elements are highlighted.

Due to the personal and material restrictions caused by the COVID-19 pandemic, the teaching of robotics has been greatly affected in recent months due to its practical nature. This work aims to explore possibilities for the continuation of this teaching remotely. A simple teaching methodology will be proposed, listed and compared simulators softwares on the most diverse platforms, and the possibility of using remote laboratories will be analyzed. The idea is to present a set of solutions, so that teachers can analyze and select the possibilities that best identify themselves and that best suit the specifics of their class.

The use of simulation and visualization tools to validate mechanical designs and programming for robots has become increasingly important. Being used in many scenarios, simulators have collaborated for research in machine learning, deep learning and training of professionals. Nowadays, with the Covid-19 pandemic and social distancing, simulators have great potential as a tool to help in the teaching of robotics. However, research indicates that the user may encounter differences between what happens in the simulator and in real life, this effect is called reality gap. This article aims to investigate the effects of this gap in an educational robotics simulator, named Virtual Robotics Toolkit (VRT), as well as its impacts on the testing of algorithms and to propose strategies to reduce the impact of this effect. Three batch tests were carried out on two different robots, both in the simulation and in the real world. By capturing data from sensors such as tachometer, infrared, gyroscope and a light sensor, it was possible to compare the performance in the two scenarios and their differences. Finally, the entire test field and models were made available along with videos of some tests.

There is a noticeable lag between Brazilian Teams and Robocup Division A teams in Small Size Soccer League (SSL). One of the main reasons is the difference in the mechanical project and how effective the dribbler and kicker systems conduct and kick the ball to other robots or the goal. This paper describes the process to develop both dribbler and kicker systems to an SSL robot, beginning with a review of Robocup Division A teams and the main Brazilian teams' projects. A 3D modeling of the dribbler and kicker systems is presented considering innovation effectiveness and space. The systems and models were evaluated via finite element simulation tests. The manufacturing process and its challenges are not in the scope of this paper due to Covid-19 limitations to lab access and will be part of future works. All parts designed are available for public use, allowing other teams to use them, modified or not, on their projects.