Social Distance and Face Mask Detection using vision-based sensors and IP cameras

Healthcare systems all over the world are strained as the COVID-19 pandemic's spread becomes more widespread. The only realistic strategy to avoid asymptomatic transmission is to monitor social distance, as there are no viable medical therapies or vaccinations for it. A unique computer vision-based framework that uses deep learning is to analyze the images that are needed to measure social distance. This technique uses the key point regressor to identify the important feature points utilizing the Visual Geometry Group (VGG19) which is a standard Convolutional Neural Network (CNN) architecture having multiple layers, MobileNetV2 which is a computer vision network that advances the-state-of-art for mobile visual identification, including semantic segmentation, classification and object identification. VGG19 and MobileNetV2 were trained on the Kaggle dataset. The border boxes for the item may be seen as well as the crowd is sizeable, and red identified faces are then analyzed by MobileNetV2 to detect whether the person is wearing a mask or not. The distance between the observed people has been calculated using the Euclidian distance. Pretrained models like (You only look once) YOLOV3 which is a real-time object detection system, RCNN, and Resnet50 are used in our embedded vision system environment to identify social distance on images. The framework YOLOV3 performs an overall accuracy of 95% using transfer learning technique runs in 22ms which is four times fast than other predefined models. In the proposed model we achieved an accuracy of 96.67% using VGG19 and 98.38% using MobileNetV2, this beats all other models in its ability to estimate social distance and face mask. © 2023 IEEE.

Smart Watch to Avoid Face Touching During Pandemic Condition

The most dangerous Coronavirus, COVID-19, is the source of this pandemic illness. This illness was initially identified in Wuhan, China, in December 2019, and currently sweeping the globe. The virus spreads quickly because it is so simple to transmit from one person to another. Fever is one of the obvious signs of COVID-19 and is one of its prevalent symptoms. The mucosal areas, such as the nose, eyes, and mouth, are among the most significant ways to catch this virus. In order to prevent and track the corona virus infection, this research suggests a face-touching detection and self-health report monitoring system. Their hygiene will immediately improve thanks to this system. In this pandemic circumstance, people use their hands in dirty environments like buses, trains, and other surfaces, where the virus can remain active for a very long time. With an accelerometer and a pulse oximeter sensor, this system alerts the user when they are carrying their hands close to their faces. © 2023 IEEE.

Four Legged Parallel Manipulator for Autonomous Delivery Robot

The COVID-19 outbreak has been designated a pandemic and is spreading quickly around the world. The industries most impacted by COVID-19, which has proved a barrier to every major business, were the e-commerce businesses that use door-to-door delivery methods. It's critical to have an unmanned strategy that can be applied to diverse sites during this key time. Although the driverless vehicle is not a novel idea, problems can occur when these systems run into the uneven pavement or unexpected obstacles. The methods for ensuring the stability of the commodities delivered by autonomous robots are discussed in this research. This mechanism guards against product damage. Additionally, a motor that stabilizes a robot's product compartment uses a gyroscope sensor to detect angular rotation and axial movement and preserve the orientation of a quadrupedal leg. In order to conduct trials that mimic problems in the real world, rectify errors, and offer solutions, a prototype model of a robot's stability platform has been created. This type of technological advancement will aid us in future efforts to combat global catastrophes. © 2023 IEEE.

Agricultural Social Networks: An Agricultural Value Chain-Based Digitalization Framework for an Inclusive Digital Economy

Sustainable agriculture is the backbone of food security systems and a driver of human well-being in global economic development (Sustainable Development Goal SDG 3). With the increase in world population and the effects of climate change due to the industrialization of economies, food security systems are under pressure to sustain communities. This situation calls for the implementation of innovative solutions to increase and sustain efficacy from farm to table. Agricultural social networks (ASNs) are central in agriculture value chain (AVC) management and sustainability and consist of a complex network inclusive of interdependent actors such as farmers, distributors, processors, and retailers. Hence, social network structures (SNSs) and practices are a means to contextualize user scenarios in agricultural value chain digitalization and digital solutions development. Therefore, this research aimed to unearth the roles of agricultural social networks in AVC digitalization, enabling an inclusive digital economy. We conducted automated literature content analysis followed by the application of case studies to develop a conceptual framework for the digitalization of the AVC toward an inclusive digital economy. Furthermore, we propose a transdisciplinary framework that guides the digitalization systematization of the AVC, while articulating resilience principles that aim to attain sustainability. The outcomes of this study offer software developers, agricultural stakeholders, and policymakers a platform to gain an understanding of technological infrastructure capabilities toward sustaining communities through digitalized AVCs.

An Efficient Artificial Intelligence based Human-Machine Interaction System

In today's computer systems, the mouse is an essential input device. Touch interfaces are high-contact planes that we use on a regular basis and frequently throughout the period. As a result, the input device gets infested with bacteria and pathogens. Despite the fact that wireless mouse have eliminated the bunch of tangled wires, there is still a desire to tap the gadget. In light of the epidemic, this proposed method employs a outlying webcam or an in-built image sensor to capture arm gestures and identify fingertip detection, allowing users to execute standard mouse activities such as left click, scrolling and other mouse activities. The algorithm is trained using machine learning with the use of image sensor and the fingers are identified efficiently. As a result, this reliance on corporeal devices to manage the computational system cancels out the requirement of man-machine interface. Thus the suggested approach will prevent the proliferation of Covid-19. © 2023 IEEE.

Optimizing Presence Sensing Lighting for Energy Efficiency and User Behavioral Needs in Small Swedish Homes

A hybrid workstyle is becoming more common post-COVID-19, and longer occupancy hours at home are increasing household electricity consumption. Small homes are regarded as a potential for improving energy efficiency in the residential sector, and a home consists of mixed-function spaces with dynamic occupancy behaviors. These underpin the opportunity to optimize presence sensing lighting in small homes for energy efficiency and user-behavioral needs. A comprehensive overview of presence sensing approaches, comparing four types of non-wearable sensors connected to home lighting is made. A bibliometric mapping of the reviewed literature visually reinforces a significant research gap that presence sensing studies were not connected to home lighting but inclined toward the commercial and institutional context. Next, a non-exhaustive example of commercially available presence sensing products applicable to residential lighting for small homes is analyzed, and their general characteristics and technologies are synthesized. The literature and product overview identified five significant product knowledge gaps. Incorporating the gathered information leads to the proposal of a conceptual flexible radar-based sensor (prototype design), addressing a wish list with three important criteria to optimize future presence sensing lighting in a mixed-function small home. Future radar sensing studies are expected to develop an anticipatory lighting system that processes real-time multi-user vital signals for smarter localized and personalized lighting options for (small) living environments.

IoT Coupled Healthcare Systems: A Bibliometric Analysis

The adoption of the Internet of Things (IoT) has revolutionized the way the health care industry works. IoT en-abled smart and connected solutions like smart sensors, wearable devices, and smart health monitoring systems are used to unleash the potential growth of the health care industry. IoT based health care solutions are on greater priority among IoT service providers since the disruptions caused by the COVID-19. According to experts, there still exist white spots in research studies on the Internet of Things (IoT) and health care Systems. The study conducted in this paper aims to explore emerging global research trends and topical focus in the field of IoT in health care System. Bibliometric analysis is used to analyze the research articles on 'Internet of Things' and 'Health care Systems' extracted from SCOPUS and WoS database using VoS Viewer tool;the analysis used to assess the growth and research trends of different research fields over a period of time. The parameters considered during analysis include year-wise citations, year-wise publications, keyword clustering analysis, author-wise analysis, country-wise research trends and publication trend over the years. The results showcased that there has been significant change in utilization of IoT in healthcare systems continuously during the period under study conducted. © 2022 IEEE.

IoT-based self-checkout stores using face mask detection

Currently, the world is witnessing a second wave of the Covid-19 pandemic, and the situation is getting worse day by day. Simple protocols like minimising human contact and wearing a mask outdoors are proving to be good measures to control the spread of the virus. We saw a huge rise in the demand for daily items and due to a lack of availability, large numbers of people gather without taking any precautions to stock essentials. This has led to the spread of the virus to a great extent. In self-checkout stores, the shopping experience is completely automated and there is no physical presence of the shop owner. The automation enables the customers to pick their goods, scan and make payments by themselves without the intervention of the owner or a cashier. In such stores there is a high chance of people not following Covid protocols. So, there is a need for a system that maintains an allowed threshold of people inside the store at any one time, thus minimizing the potential dangerous human contact at all possible cases. We propose an IoT-Based Self-Checkout Store Using Mask Detection. The primary goal of this project is to create a safe environment for the consumers who visit the shop, by keeping a check on the number of customers present at the store and ensuring that each and every customer is following the protocol of wearing a mask. The system consists of two parts, the face mask detection and the customer count. For the mask detection part, deep learning algorithms like CNN are used to generate a model that helps detect a mask, and for the customer count part, a threshold value is set, which gives us the maximum number of people allowed inside the store at a time. The PIR sensors detect the entry and exit of customers and help regulate the count below the threshold. So once the face mask detection of the customer is complete and the number of people present inside the store is checked, the system takes the decision of either allowing the customer inside or asking him or her to wait. This project is designed to provide a solution to the current real-world problem using minimally efficient technology with high accuracy. © 2023 Scrivener Publishing LLC. All rights reserved.

VALIDITY AND RELIABILITY OF MEASUREMENT OF PERIPHERAL OXYGEN SATURATION DURING THE 6-MINUTE WALK TEST IN PATIENTS WITH SYSTEMIC SCLEROSIS

BackgroundThe 6-Minute Walk Test (6MWT) is a standardised method routinely used to screen for and monitor interstitiel lunge disease and/or pulmonary arterial hypertension in patients with systemic sclerosis (SSc). Studies shows that esaturations during the 6MWT are associated with severity of pulmonary manifestations in patients with SSc [1]. Digital sensors are commonly used to measure peripheral oxygen saturation (SpO2) during the 6MWT. However, digital-based sensors may have important limitations in patients with SSc due to disease-related microangiopathy, Raynaud's phenomenon, sclerodactyly and motion artifacts during the 6MWT [2]. Sensors located at more central body positions may therefore be more accurate as these as less prone to Raynaud attacks.ObjectivesTo determine the validity and re-test reliability of peripheral oxygen saturation measured at the finger, forehead, and ear during the 6MWT in patients with SSc.Methods82 patients with SSc had an arterial line placed while performing the 6MWT. Peripheral oxygen saturation was simultaneously measured by finger, forehead, and earlobe sensors and compared to the arterial oxygen saturation (SaO2) measured before and after the 6MWT. 40 patients repeated the 6MWT one week later. We used Bland-Altman plots to display the agreement between SpO2 and SaO2, and between the minimal SpO2 (minSpO2) one week apart. The intraclass correlation coefficient (ICC, 95% confidence interval 95% CI]) for repeated measurement of minSpO2 was calculated.ResultsThe mean difference (SpO2 - SaO2, ± standard deviation [SD]) after the 6MWT was –3.3% (±4.82), 0.15% (±1.55), and 1.36% (±1.93) for the finger, forehead, and earlobe, respectively (Table 1).The finger minSpO2 also demonstrated the poorest re-test reliability: The mean difference in minSpO2 (visit2-visit1, ±SD) was 1.28% (±5.3), 0.74% (±4.36) and –1.10% (±2.87),). The ICC (95% CI) showed good agreement using the ear and forehead probe (ICCear = 0.89 [0.80;0.94];ICCforehead = 0.88 [0.60;0.87]), while a modest reliability was found using the finger probe (ICCfinger = 0.65 [0.43;0.80]).ConclusionPeripheral oxygen saturation should be measured using either the earlobe or forehead during the 6MWT in patients with SSc.References[1]Villalba, W. O. et al. Six-minute walk test for the evaluation of pulmonary disease severity in scleroderma patients. Chest 131, 217–222 (2007).[2]Pathania, Y. S. Alternatives for erroneous finger probe pulse oximetry in systemic sclerosis patients during COVID-19 pandemic. Rheumatol. Int. 41, 2243–2244 (2021).Table 1.Validity and re-test reliability of peripheral oxygen during the 6MWT (n= 82)Finger probeForehead probeEar probeMean difference SpO2 - SaO2  Mean difference pre-test (+/-SD)–0.68% (±1.88)0.13% (±1.26)1.54% (±0.69)  Mean difference post--test (+/-SD)–3.30% (±4.82)0.15% (±1.55)1.36% (±1.93)Mean difference of the minSpO2 (visit2-visit1)  Mean difference (±SD)1.28% (±5.3)0.74% (±4.36)1.10% (±2.87)Abbreviations: SpO2, Peripheral oxygen saturation;SaO2, Arterial oxygen saturation;SD, Standard deviation.Acknowledgements:NIL.Disclosure of InterestsAmanda Lynggaard Riis: None declared, Esben Naeser Paid instructor for: Boehringer Ingelheim Denmark, Katja Thorup Aaen: None declared, Henrik Hovgaard: None declared, Peter Juhl-Olsen: None declared, Elisabeth Bendstrup Speakers bureau: Hoffman-la-Roche.Boehringer Ingelheim.Glaxo Smith Kleine.Daichii Sankyo, Klaus Soendergaard Speakers bureau: Boehringer Ingelheim, Consultant of: Boehringer Ingelheim, Grant/research support from: Boehringer Ingelheim.

Infrared Temperature Detection Using MLX90614 Sensor for Wearable Applications

Body temperature is a significant vital sign that can provide great insight as to the state of health of a person. Nowadays, body temperatures are monitored as often as a precaution for the COVID-19 virus. This can be achieved with the use of wearables, which can be non-invasive and convenient for anybody to use. This study aims to design and construct a wearable that can accurately detect the body temperature of a person using the MLX90614 sensor as well as an I2C enabled LCD to allow the user to monitor their temperature at a moment's notice. © 2023 IEEE.

Automating Biopharma Manufacturing

"With the advance of data science enabling factors such as easy access to scalable memory and computing resources;our growing competence in collecting, storing, and contextualizing data;advances in robotics;[and] the quickly evolving method landscape driven by the open-source community, the benefits of automation and simulation are becoming accessible in the notoriously complicated realm of biopharma manufacturing," says Marcel von der Haar, head of product strategy data analytics at Sartorius. "Plug-and-play" capabilities of automation systems, which enable flexible manufacturing and faster technology transfer, are more important than ever, he says. Walvax Biotech's new COVID-19 mRNA vaccine plant in China is another example of an intelligent and digital plant;it uses Honeywell's batch process control, building and energy management solution systems, and digital twins to monitor assets (5). "Automation brings in the data for machine learning to model the dynamic processes of cell growth and map it against the multiple dimensions provided by advanced sensors," explains Brandl.

Digitalization Moves Forward in Pharma Equipment and Processes

Digital technologies that could meet these new challenges and aid manufacturing scale-up and speed to market, such as automated digital data collection and augmented and virtual reality (AR/VR) remote collaboration tools, were already available and had been adopted by some, but the new demand spurred greater adoption. "There is a cultural aspect to digitalization because it's a significant investment that results in changes to the operational structure of a facility;it is beneficial when the digitalization comes from the top," explains Yvonne Duckworth, automation engineer and Industry 4.0 subject matter expert at the CRB Group, a life sciences engineering and construction company. Machine sensors and process analytical technology (PAT) instruments can communicate directly with data collection systems using the NoT. Efficient development and tech transfer for mRNA vaccine manufacturing The data analysis and clear communication allowed by digital tools has demonstrated its benefits for process development and technical transfer, making time to market faster.

Face Mask And Body Temperature Detection In Sensor Enabled Automated Door Control System

Developing an automatic door-opening system that can recognize masks and gauge body temperature is the aim of this project. The new Corona Virus (COVID-19) is an unimaginable pandemic that presents the medical industry with a serious worldwide issue in the twenty-first century. How individuals conduct their lives has substantially changed as a result. Individuals are reluctant to seek out even the most basic healthcare services because of the rising number of sick people who pass away, instilling an unshakable terror in their thoughts.This paper is about the Automatic Health Machine (AHM). In this dire situation, the government provided the people with a lot of directions and information. Apart from the government, everyone is accountable for his or her own health. The most common symptom of corona infection is an uncontrollable rise in body temperature. In this project, we create a novel device to monitor people's body temperatures using components such as an IR sensor and temperature sensor. © 2023 IEEE.

Survival of the fittest: the multiple paths of entrepreneurial leadership driving adaptive innovation in uncertain environment

PurposeThis study aims to investigate the multiple influence paths or underlying mechanisms of entrepreneurial leadership (EL) on adaptive innovation from the perspectives of organizational learning and resource management, drawing on complex adaptive system theory.Design/methodology/approachWith a questionnaire survey of 317 senior and middle managers from different firms in China, structural equation modeling was used to test the hypothesized conceptual model, and bootstrapping method was employed to examine the multiple mediating effects.FindingsResults indicate that EL has a significant and positive effect on adaptive innovation. This relationship is partially mediated through exploitative learning, exploratory learning, resource bricolage and boundary-spanning integration, respectively. The impact of EL on adaptive innovation is also sequentially transmitted through exploitative learning and resource bricolage or exploratory learning and boundary-spanning integration.Originality/valueAdaptive innovation has become a firm competition strategy to cope with dynamic changes in current uncertain environment where EL can play its effectiveness to engage firms in such innovation activities. However, the question of why and how EL drives adaptive innovation has yet to be discussed. This study highlights the innovation effectiveness of EL and the triggering process of adaptive innovation, and contributes to several countermeasures for firms to implement leadership and innovation practices responding to uncertain environment.

Development of Data Logger for COVID Vaccine Temperature Monitoring System

The Data Logger (DL) is a unique tool created to carry out the typical duty of gathering data in a specific area. This common task can include measuring humidity, temperature, pressure or any other physical quantities. Due to the current pandemic situation, its use in temperature monitoring of Covid vaccine will be crucial. According to World Health Organization (WHO) guidelines, COVID vaccine can be stored and transported at -80 °C, -20°C and +2-8°C and shelf life is reduced as vaccine is transferred from one storage temperature to another. So cost effective, efficient and standalone Data Logger (DL) is the need of the hour. The Data logger is proposed to be developed with the use of ESP8266 Node MCU microcontroller. It takes power from a 5V Battery. DS18B20 sensor will be used for temperature sensing. Here we will use Wi-Fi module of ESP8266 Node MCU to send the temperature data from sensor to the Google Sheet over the internet. This real time data will be stored in the format of time and month/date/year. Data logged in Google Sheet will be displayed to the user with the help of graphical user interface (GUI) which is developed using PYTHON scripting language. GUI will allow user to interact with Data Logger through visual graphs. The Data Logger components are mounted on a double layered PCB. © 2022 IEEE.

Multiple Fano Resonances in Plasmonic Waveguide Based Cavity and Detection of Pathogenic Virus

A technique is implemented for the generation of multiple Fano-resonances in a plasmonic waveguide based rectangular cavity. A rectangular cavity provides four Fano peaks which can further be increased to nine by inserting the metallic bars in it. The trapped surface plasmon polaritons by metallic bars cause the generation of multiple Fano peaks over the wavelength range of 450 nm - 1300 nm. The obtained response is validated through Fano profile and Fano shape parameter is calculated for each resonance peak. The performance of the proposed device is numerically studied as refractive index sensor and method for analyzing the detection of pathogenic virus like SARS-Cov-2 is reported. Out of nine Fano peaks, the best values of sensing performance indices are obtained with full-width, half-maxima of 1.7 nm, quality factor of 405, sensitivity of 1145.71 nm/RIU and figure of merit of 393.25 RIU-1. IEEE

COVID bell - A smart doorbell solution for prevention of COVID-19

The article introduces a novel strategy for efficiently mitigating COVID-19 distribution at the local level due to contact with any surfaces. Our project aims to be a critical safety shield for the general people in the fight against the epidemic. An ultrasonic sensor is integrated with the automated doorbell system to ring the doorbell with a hand motion. A temperature sensor Mlx90614 is also included in the system, which records the temperature of the person standing in front of the door. The device also includes a camera module that captures the image of the person standing at the front entrance. The captured image is processed through an ML model which runs at over 30 fps to detect whether or not the person is wearing a mask. The image and the temperature of the person standing outside are sent to the owner through the configured iOS application. If the person outside is wearing a mask, one can open the door through the app itself and permit the entry of the person standing outside thereby integrating the edge device with an app for a better user experience. The system helps in reducing physical contact, and the results obtained are at par with the already existing solutions and provide a few advantages over them. © 2023 the author(s), published by De Gruyter.

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

3D-Printed Face Mask with Integrated Sensors as Protective and Monitoring Tool

The outbreak of the recent Covid-19 pandemic changed many aspects of our daily life, such as the constant wearing of face masks as protection from virus transmission risks. Furthermore, it exposed the healthcare system's fragilities, showing the urgent need to design a more inclusive model that takes into account possible future emergencies, together with population's aging and new severe pathologies. In this framework, face masks can be both a physical barrier against viruses and, at the same time, a telemedical diagnostic tool. In this paper, we propose a low-cost, 3D-printed face mask able to protect the wearer from virus transmission, thanks to internal FFP2 filters, and to monitor the air quality (temperature, humidity, CO2) inside the mask. Acquired data are automatically transmitted to a web terminal, thanks to sensors and electronics embedded in the mask. Our preliminary results encourage more efforts in these regards, towards rapid, inexpensive and smart ways to integrate more sensors into the mask's breathing zone in order to use the patient's breath as a fingerprint for various diseases. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

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.