The tactile dimension: a method for physicalizing touch behaviors

Traces of touch provide valuable insight into how we interact with the physical world. Measuring touch behavior, however, is expensive and imprecise. Utilizing a fluorescent UV tracer powder, we developed a low-cost analog method to capture persistent, high-contrast touch records on arbitrary objects. We describe our process for selecting a tracer, methods for capturing, enhancing, and aggregating traces, and approaches to examining qualitative aspects of the user experience. Three user studies demonstrate key features of this method. First, we show that it provides clear and durable traces on objects representative of scientific visualization, physicalization, and product design. Second, we demonstrate how this method could be used to study touch perception, by measuring how task and narrative framing elicit different touch behaviors on the same object. Third, we demonstrate how this method can be used to evaluate data physicalizations by observing how participants touch two different physicalizations of COVID-19 time-series data. © 2023 ACM.

Evaluation of a Low-Cost Air Renewal System for Indoor Air Quality Control in a Climate Chamber

There is a growing concern about Indoor Environmental Quality (IEQ) in buildings as humans are spending longer in indoor environments, whether this is associated or not with climate change and vulnerability to extreme weather events. In the wake of the COVID pandemic, the need for indoor air quality control is likely to increase, the result of many adaptations in home environments to switch to remote work. In hot countries in the Global South, one of the alternatives is split A/C units with limited air renewal. While, odorless and colorless CO2, commonly generated by occupants through respiration, is among the relevant indoor air pollutants. The purpose of this study is to evaluate a low-cost, responsive air-renewal system in a climate chamber equipped with a standard split A/C unit. The results show the system's feasibility in curbing IAQ concerns and also highlight the risk of negative impacts on indoor thermal conditions and on energy consumption on using A/C. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

A Low-Cost Wireless Body Area Network for Human Activity Recognition in Healthy Life and Medical Applications

Moved by the necessity, also related to the ongoing COVID-19 pandemic, of the design of innovative solutions in the context of digital health, and digital medicine, Wireless Body Area Networks (WBANs) are more and more emerging as a central system for the implementation of solutions for well-being and healthcare. In fact, by elaborating the data collected by a WBAN, advanced classification models can accurately extract health-related parameters, thus allowing, as examples, the implementations of applications for fitness tracking, monitoring of vital signs, diagnosis, and analysis of the evolution of diseases, and, in general, monitoring of human activities and behaviours. Unfortunately, commercially available WBANs present some technological and economic drawbacks from the point of view, respectively, of data fusion and labelling, and cost of the adopted devices. To overcome existing issues, in this paper, we present the architecture of a low-cost WBAN, which is built upon accessible off-the-shelf wearable devices and an Android application. Then, we report its technical evaluation concerning resource consumption. Finally, we demonstrate its versatility and accuracy in both medical and well-being application scenarios. Author

A Simulation of a Design and Implementation of a New Low- Cost Prototype Portable Smart Ventilator

The outbreak of the Covid-19 virus prompted many engineers and researchers around the world to seek to develop mechanical ventilation devices and make them easy to use and affordable. This paper presents a simulation model for a group of medical sensors and gives very accurate results. This model contributes to the development and improvement of the artificial breathing system by comparing the results between the simulation model and the realistic response of the human lung. © 2023 IEEE.

Managing indoor air quality in nursery and primary schools with low-cost solutions

This study aimed to evaluate the feasibility of using low-cost solutions to monitor and mitigate PM2.5 and PM10 concentrations in nursery and primary schools in Porto (Portugal). Three periods were considered: i) early 2020 (before COVID-19 pandemic), ii) early 2021 (during COVID-19 pandemic, with mitigation measures to prevent SARS-CoV-2 spread);and iii) in the middle of 2021 (additionally using a low-cost portable air cleaner). PM2.5 and PM10 were continuously monitored with a low-cost sensing device for at least two consecutive days in five classrooms. In general, the lowest PM concentrations were observed in the third period. Concentrations reduced up to 63% from the second to the third period. The application of low-cost solutions for monitoring and mitigating PM levels seems to be an effective tool for managing indoor air in schools. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Design and Development of Toroidal Core Winding Machine with Digital Interface

The small size and inherent superior electrical characteristics of a toroid has made it the first choice for many Original Equipment Manufacturers (OEMs). However, the lack of knowledge regarding the toroidal coil winding equipment is still hampering the growth of toroid as the first choice for transformers, inductors and other electrical applications. Additionally, due to Covid-19 pandemic and lockdown situation, small scale companies are lacking skilled manpower for the high precision task of toroidal core winding and taping. Although the machine is readily available in the market, the cost is still very high. Toroidal core winding machine is an equipment used for the purpose of winding toroidal cores which is used in various electrical machines such as current transformers, power transformers, isolation transformers, inductors and chokes, auto transformers, etc. This project aims to develop a low-cost toroidal winding machine with a user-friendly digital interface for selection of winding parameters as per the user input. The winding machine developed in this project is efficient and reliable with high-speed performance and negligible error. © 2022 IEEE.

Mobile Information System for Determining the Level of Creatine in Food Products

The study of food products to determine the level of creatine in them is an actual task, taking into account the need for this substance for patients with Covid'19 and spinal muscular atrophy. The purpose of our research is to develop a mobile information system for determining the level of creatine in food products. The developed method for determining the level of creatine in food products by the user and the method for determining the level of creatine in food products using a mobile information system provide the user with the opportunity to quickly, conveniently, cheaply and effectively assess the presence and level of creatine in any food products, on the basis of which to build a rational diet from the point vision of body saturation with creatine. The proposed mobile information system for determining the level of creatine in food products provides convenience, low-cost, celerity, miniaturization and automation for measurement of concentration of creatine in any food products. The conclusion obtained from the system regarding the presence and level of creatine in this or that food product is useful and extremely important when preparing the diet of patients, especially patients with Covid'19 and/or spinal muscular atrophy. The proposed approach and mobile information system for determining the level of creatine in food products can be used not only for drawing up the diet of patients, especially patients with Covid'19 and/or spinal muscular atrophy, from the point vision of body saturation with creatine, but also for example, to check the quality of meat products. © 2023 Copyright for this paper by its authors.

Fusion-Based Segmentation and Classification of Novel Coronavirus or Pneumonia from Chest X-ray Images Using Machine Learning Techniques

The deadfall widespread of coronavirus (SARS-Co V-2) disease has trembled every part of the earth and has significant disruption to health support systems in different countries. In spite of such existing difficulties and disagreements for testing the coronavirus disease, an advanced and low-cost technique is required to classify the disease. For the sense of reason, supervised machine learning (ML) along with image processing has turned out as a strong technique to detect coronavirus from human chest X-rays. In this work, the different methodologies to identify coronavirus (SARS-CoV-2) are discussed. It is essential to expand a fully automatic detection system to restrict the carrying of the virus load through contact. Various deep learning structures are present to detect the SARS-CoV-2 virus such as ResNet50, Inception-ResNet-v2, AlexNet, Vgg19, etc. A dataset of 10,040 samples has been used in which the count of SARS-CoV-2, pneumonia and normal images are 2143, 3674, and 4223 respectively. The model designed by fusion of neural network and HOG transform had an accuracy of 98.81% and a sensitivity of 98.65%. © 2022 IEEE.

The influence of supply chain risk management in healthcare supply chains performance

The challenges imposed by the business environment increasingly obligate supply chains to seek lower costs while maintaining high service levels. Healthcare supply chains face additional challenges since their main indicator is to save lives and provide care, nonetheless, keeping the revenue flow to support the activities. The covid-19 pandemic evidenced that a severe rupture in healthcare chains generates rupture in all other supply chains. In this sense, our paper has the objective of presenting a conceptual healthcare supply chain performance framework empirically validated by structural equation modelling. Our survey data were processed through the covariance-based structural equation modelling method, adopted for assessing the causal connection among the constructs. The paper revealed a relationship of supply chain integration, supply chain risk management, and supply chain 4.0 (antecedents) with healthcare supply chain performance (consequent). The literature contributions of this paper are (i) developing and validating a new scale for each construct;(ii) finding evidence of the causal relationships between the factors;(iii) measuring how the constructs influence the healthcare supply chain performance in both public and private healthcare sectors and providing discussion and tools to improve these results;(iv) this work empirically tested a theoretical framework;(v) the study reveals that the sector (public or private) has a moderating effect on all the constructs. Furthermore, the results of this study help to address some literature gaps identified by scholars having the potential to serve as a guide to organisations that are willing to implement these practices. Lastly, we recommend that HC supply chain managers consider the implementation of robust initiatives regarding SCRM, SCI, and SC40. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

A Low-cost Handheld Reconfigurable Impedimetric Readout System for Diagnostics of Viral Infections

This paper presents a portable impedimetric biosensor for detecting infectious diseases such as SARS-CoV-2 Infections. A bio-ready sensing electrode functionalized with SARS-CoV-2 nucleocapsid antibody was employed to quantitatively convert the concentration of nucleocapsid protein (N-protein) into impedance changes. In this paper, we proposed a readout system with a dynamic input range of 200 Ωto 1 MΩmagnitude and 0 to 180°phase. The resolution of this device is 1% and 6.5°for measuring the magnitude and phase, respectively. Herein we demonstrate and discuss the proposed system’s functionality, sensitivity, and selectivity using the clinical swab samples. As per these results, this readout system is suitable for the detection of N-protein ranging up to 10,000 pg/mL with a resolution of 56 fg/mL. The proposed impedimetric sensing system can be adopted for the detection of infectious diseases in the future. This low-cost (<$80) device using off-the-shelf is a unique candidate for batch production purposes during urgent pandemic situations. IEEE

People Counting in the Times of Covid-19

Estimating the number of people within a public building with multiple entrances is an interesting problem, especially when limitations on building occupancy hold as during the Covid-19 pandemic. In this article, we illustrate the design, prototyping and assessment of an open-source distributed Cloud-IoT service that performs such a task and detects crowd formation via EdgeAI, also accounting for privacy and security concerns. The service is deployed and thoroughly assessed over a low-cost Fog infrastructure, showing an average accuracy of 94%. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Rapid Convergence: The Outcomes of Making PPE During a Healthcare Crisis

The U.S. National Institute of Health (NIH) 3D Print Exchange is a public, open-source repository for 3D printable medical device designs with contributions from clinicians, expert-amateur makers, and people from industry and academia. In response to the COVID-19 pandemic, the NIH formed a collection to foster submissions of low-cost, locally manufacturable personal protective equipment (PPE). We evaluated the 623 submissions in this collection to understand: what makers contributed, how they were made, who made them, and key characteristics of their designs. We found an immediate design convergence to manufacturing-focused remixes of a few initial designs affiliated with NIH partners and major for-profit groups. The NIH worked to review safe, effective designs but was overloaded by manufacturing-focused design adaptations. Our work contributes insights into: the outcomes of distributed, community-based medical making;the features that the community accepted as "safe"making;and how platforms can support regulated maker activities in high-risk domains. © 2023 Copyright held by the owner/author(s).

Low-Cost Wearable Device to Provide an Effective Solution for Contact Tracing and Logistics

The paper introduces a low-cost wearable band that does the tedious, repetitive task of entering your required details in any shop or organization, as well as keeping a record of all the people you have come in contact with. There are two aspects of our device:1)If a person enters a shop with our device, the band will transmit the required information of the wearer to the reader kept at the shopkeeper's side wirelessly. The transmitted information will include the wearer's information (as per government guidelines) masked in the band's Unique ID along with their temperature status (whether having a temperature above 100°F or not).2)When two persons come near each other over a distance of 6 feet, the unique ID broadcasted from each other's bands gets stored in the other's band. If any of them tests positive for Coronavirus Disease (COVID-19) or similar diseases, his/her unique ID can be used to trace primary contacts and take appropriate steps to contain further spread.Privacy is key! So, we are reengineering the primary concept of contact tracing and logistics while keeping the user's information safe and secure. © 2023 IEEE.

Review on Design and Performance of the Medical Ventilators

Ventilators we are available with have several drawbacks such as difficult to port, expensive and meant to be operated by professionals which create hardness in fighting with medical care. Thus, it creates suffering for people in the pandemic like COVID19. So, it is required to develop a ventilator that can be affordable, easy to port and install. We aimed to design a IoT based ventilator system using various electronic devices such as microcontroller and sensors that could monitor patient's body status. People suffering from COVID19 or any lung disease find difficulty in breathing so in such condition of emergency this smart ventilator system can be used. Ambu bag is used to provide certain volume of air that is pressed by using motor mechanism. A portable low-cost ventilator with computerized controlling and feedback system is installed. Ventilator designed can be connected to an interface for smart functioning. This paper provides us with different methods to monitor the patient's health condition by measurement of pressure, level of breathing to know whether the condition is healthy or unhealthy. The designing and developing of low-cost portable ventilator deliver breaths to patients when Ambu bag is compressed by using a piston connected to servo motor whose speed can be varied. Input of the designed system is patient's heart beat and breathing rate and the volume of oxygen provided to patient's lung with required beathing rate is the output of the system. PID (proportional Integral Derivative) and Full state feedback H2 controllers are used for the performance analysis of the system. Result of this review paper is found that a low-cost ventilator is developed removing all the possible shortcomings of existing conventional ventilator. Ventilator designed is portable and smart by using Arduino, servo motor and ambu bag preferred for emergency uses and available for clinical application. © 2023 IEEE.

Low-cost heat exchanger benches for remote operation

The COVID-19 pandemic created significant challenges in operating the lab component of undergraduate courses and promoting active learning, with only a short time available to implement alternative teaching methods. In this work a low-cost platform for distance operation and assessment of replaceable bench-scale heat exchangers was developed to provide students an opportunity to observe the transient and steady-state behavior of heat exchangers while unable to access lab facilities. Each workbench had a new material cost of approximately C$5 000. Operation of physical equipment provided students the opportunity to observe non-ideal behavior and compare various heat transfer correlations which may not be seen in process simulators. The developed platform implemented an Arduino microcontroller for low-cost process control. Equipment was seamlessly slotted in to the existing course upon the return to on-campus learning and provided a more stable system when compared to previously existing lab experiments. Most learning outcomes were observed in remote and in-lab experiments and challenges faced in remote operation are highlighted. No statistically significant difference was observed in student performance between students completing lab experiments remotely and students completing experiments in-lab. © 2023 Institution of Chemical Engineers

N/MEMS Biosensors: An Introduction

In the twenty-first century, biosensors have gathered much wider attention than ever before, irrespective of the technology that promises to bring them forward. With the recent COVID-19 outbreak, the concern and efforts to restore global health and well-being are rising at an unprecedented rate. A requirement to develop precise, fast, point-of-care, reliable, easily disposable/reproducible and low-cost diagnostic tools has ascended. Biosensors form a primary element of hand-held medical kits, tools, products, and/or instruments. They have a very wide range of applications such as nearby environmental checks, detecting the onset of a disease, food quality, drug discovery, medicine dose control, and many more. This chapter explains how Nano/Micro-Electro-Mechanical Systems (N/MEMS) can be enabling technology toward a sustainable, scalable, ultra-miniaturized, easy-to-use, energy-efficient, and integrated bio/chemical sensing system. This study provides a deeper insight into the fundamentals, recent advances, and potential end applications of N/MEMS sensors and integrated systems to detect and measure the concentration of biological and/or chemical analytes. Transduction principle/s, materials, efficient designs, including readout technique, and sensor performance are explained. This is followed by a discussion on how N/MEMS biosensors continue to evolve. The challenges and possible opportunities are also discussed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

People Counting in the Times of Covid-19

Estimating the number of people within a public building with multiple entrances is an interesting problem, especially when limitations on building occupancy hold as during the Covid-19 pandemic. In this article, we illustrate the design, prototyping and assessment of an open-source distributed Cloud-IoT service that performs such a task and detects crowd formation via EdgeAI, also accounting for privacy and security concerns. The service is deployed and thoroughly assessed over a low-cost Fog infrastructure, showing an average accuracy of 94%. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Bioinspired CNN Approach for Diagnosing COVID-19 Using Images of Chest X-Ray

Introduction: The provision of medical facilities needed for COVID-19 diagnosis is a global concern. They must be a powerful tool for detecting and diagnosing the virus quickly using a variety of tests, as well as low-cost advancements. Whereas a chest X-ray image is an effective screening technique, the image acquisition by the instruments must be read appropriately and quickly if multiple tests are performed. Objectives: COVID-19 causes continuous respiratory parenchymal ground glass and integrates respiratory opacity, with a curved shape and peripheral pulmonary dissemination in some cases, which is difficult to anticipate earlier on. In this chapter, we intend to construct a good platform to identify COVID-19 characteristics from the image of chest X-ray to aid in early analysis. Methods: In particular, based on the Cuckoo search method, this chapter provides a bioinspired CNN-based model for COVID-19 diagnosis. This method identifies different deep learning strategies of COVID-19 patients' chest X-ray images for accurate infection identification. The suggested model's performance is estimated using the Cuckoo search approach. Furthermore, the bioinspired CNN characteristics are fine-tuned using optimization algorithm. Rigorous testing reveals that suggested method may accurately categorize chest X-ray images with high performance, remembrance, and sensitivity. Results: As a result, the suggested approach can be used to classify COVID-19 diseases from chest X-ray images in real time and also accuracy will be validated. Conclusion: Finally, the investigation of comparison results illustrates the Cuckoo algorithm is realized to determine the interested regions of the COVID-19 x-ray images. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

MEMs Based Low-Cost Urban Noise Monitoring: Tests and Case Study

Noise pollution has been one of the main causes of citizens' discomfort in the urban centers in Brazil, an issue enhanced by the Covid pandemic that resulted in an increase of noise complaints, especially those related to noise from construction sites. This context triggered the construction industry to pursue solutions to understand the acoustic reality and minimize the impacts through regulations that require long-term noise measurements. Due to the necessity of a comprehensive evaluation in several locations, class 1 Sound Level Meters measurement systems can hardly be considered because of their high costs. This paper discusses the practical implementation of MEMs in a low-cost monitoring system for urban noise, focusing on construction sites. The prototype, based on a Raspberry Pi (a single-board computer model widely used in IoT projects) and a MEMs microphone with I2S interface for high-fidelity digital audio communication, was compared in a controlled environment to a Sound Level Meter of Class 1 through validation tests, such as calibration, frequency response, and dynamic range. Field measurements were also carried out in typical urban noise-generating sound environments. © 2022 Internoise 2022 - 51st International Congress and Exposition on Noise Control Engineering. All rights reserved.

A Low-Cost IoT System for Monitoring Air Quality in Indoor Working Places

This paper presents a development of internet of things (IoT)-based indoor air quality monitoring system. The system is purposed to monitor quality of air in offices. It is to assure the health and safety of the working place which is especially being a big concern during the COVID-19 pandemic. Implementing the IoT concept allows to do monitoring from anywhere at anytime. A prototype of the monitoring system is built using three major components, such as an air quality sensor (BME680), a microcontroller (NodeMCU ESP-12), and an IoT cloud platform (ThingSpeak). The experimental test result shows that system was able to monitor the air temperature, air humidity, air pressure, IAQ (indoor air quality) index, carbon dioxide quantity, and VOC (volatile organic compound). These data is presented real-time in a web application and accessible from anywhere by using computers or smartphones. © 2022 IEEE.