The Internet of Things Security and Privacy: Current Schemes, Challenges and Future Prospects

The Internet of Things devices and users exchange massive amount of data. Some of these exchanged messages are highly sensitive as they involve organizational, military or patient personally identifiable information. Therefore, many schemes and protocols have been put forward to protect the transmitted messages. The techniques deployed in these schemes may include blockchain, public key infrastructure, elliptic curve cryptography, physically unclonable function and radio frequency identification. In this paper, a review is provided of these schemes including their strengths and weaknesses. Based on the obtained results, it is clear that majority of these protocols have numerous security, performance and privacy issues

The Internet of Things in Healthcare. An Overview

La prestación de servicios de salud está experimentando enormes cambios alrededor del mundo. El envejecimiento de la población, la creciente incidencia de enfermedades crónicas, y la escasez de recursos se están convirtiendo en una carga pesada para los actuales sistemas de salud y podrían comprometer la prestación de servicios de salud en las próximas décadas. Por otro lado, la creciente popularidad de dispositivos para el cuidado de la salud y el bienestar, junto con avances en comunicaciones inalámbricas y en sensores abren la puerta a nuevos modelos para la prestación de servicios de salud respaldados por el Internet de las cosas (IoT). Este artículo presenta una revisión general de las tendencias que están impulsando el desarrollo de aplicaciones para el cuidado de la salud basadas en IoT, y las describe brevemente a nivel de sistema.The provision of healthcare is experimenting enormous changes worldwide. Population ageing, rising incidence of chronic diseases, and shortages of resources are placing a heavy burden in current healthcare systems and have the potential to risk the delivery of healthcare in the next few decades. On the other hand, the growing popularity of smart devices for healthcare and wellness, along with advances in wireless communications and sensors are opening the door to novel models of health care delivery supported by the Internet of things (IoT). This paper presents a review of the trends that are driving the development of IoT-based applications for healthcare and briefly describe them at a system level

Framework for propagating stress control message using heartbeat based IoT remote monitoring analytics

Abnormal level of stress is the root indicator factor to have significant impact over the health of heart and there is a close relationship between the stress levels with heart rate. Review of the existing literature showcase that there has been various work that has been carried out towards investigation of considering heart rate with an internet-of-things (IoT) system. Apart from this, existing system doesnt offer any instantaneous solution where certain intimation is offered in real-time to the user with wearables as a solution to control the stress condition. Therefore, the current paper introduces a novel framework where the sampled heart rates of the patients are captured by IoT deivices. The aggregated data are further forwarded to the cloud analytic system that uses correlation to extract the appropriate message. The system after being applied with teh machine learning approach could further extract the elite outcome followed by forwarding the contextual data to teh user. Using an analytical modelliig, the proposed system shows that it offers better accuracy and reduced processing time when compared with other machine learning approach and thereby it proves to be cost effective solution in IoT system over medical case study

Fit-Twin: A Digital Twin of a User with Wearables and Context as Input for Health Promotion

Digital health contributes to health promotion by empowering the user with the holistic view of their health. Health promotion is to enable the user to take control over their health. The availability of wearables has contributed to the shift in healthcare, that is more connected, predictive, and proactive. Proactive in healthcare is to predict and prevent a situation, beforehand. This shift in healthcare puts the user in charge of most healthrelated decisions. Innovative technologies like AI already contribute to the cause by applying reasoning and negotiation to the collected health data to provide timely interventions to the user. The availability of realtime data from sensors that the user wears all the time allows more opportunities with new health insights. One such prospect is the use of digital twins, which provides personalization and precision. Digital twins also allow risk-free modelling for more accurate outcomes. A user digital twin is not just a virtual replica, but it combines all the factors that can impact the user. The context of the user is a prominent factor in healthcare. The paper establishes the need for digital twins in health promotion. In this paper, a Fit-twin is presented that mimics a user with wearables and the user context as input. The Fit-twin is implemented using Azure digital twins, Fitbit charge, and local context API. This allows one-way communication between the user and the Fit-twin. The outcome is a user digital twin that can be used for health promotion by applying predictive capabilities

Soft Transducer for Patient’s Vitals Telemonitoring with Deep Learning-Based Personalized Anomaly Detection

This work addresses the design, development and implementation of a 4.0-based wearable soft transducer for patient-centered vitals telemonitoring. In particular, first, the soft transducer measures hypertension-related vitals (heart rate, oxygen saturation and systolic/diastolic pressure) and sends the data to a remote database (which can be easily consulted both by the patient and the physician). In addition to this, a dedicated deep learning algorithm, based on a Long-Short-Term-Memory Autoencoder, was designed, implemented and tested for providing an alert when the patient’s vitals exceed certain thresholds, which are automatically personalized for the specific patient. Furthermore, a mobile application (EcO2u) was developed to manage the entire data flow and facilitate the data fruition; this application also implements an innovative face-detection algorithm that ensures the identity of the patient. The robustness of the proposed soft transducer was validated experimentally on five individuals, who used the system for 30 days. The experimental results demonstrated an accuracy in anomaly detection greater than 93%, with a true positive rate of more than 94

Intelligent IoT Framework for Indoor Healthcare Monitoring of Parkinson's Disease Patient

Parkinson’s disease is associated with high treatment costs, primarily attributed to the needs of hospitalization and frequent care services. A study reveals annual per-person healthcare costs for Parkinson’s patients to be 21,482,withanadditional29,695 burden to society. Due to the high stakes and rapidly rising Parkinson’s patients’ count, it is imperative to introduce intelligent monitoring and analysis systems. In this paper, an Internet of Things (IoT) based framework is proposed to enable remote monitoring, administration, and analysis of patient’s conditions in a typical indoor environment. The proposed infrastructure offers both static and dynamic routing, along with delay analysis and priority enabled communications. The scheme also introduces machine learning techniques to detect the progression of Parkinson’s over six months using auditory inputs. The proposed IoT infrastructure and machine learning algorithm are thoroughly evaluated and a detailed analysis is performed. The results show that the proposed scheme offers efficient communication scheduling, facilitating a high number of users with low latency. The proposed machine learning scheme also outperforms state-of-the-art techniques in accurately predicting the Parkinson’s progression

Use of ICT to Confront COVID-19

The impact of COVID-19 outbreak has now become of grave concern for virtually every country in the world, and forced a majority of countries into partial or complete lockdowns. WHO reports show more than 150 Million confirmed cases, with a death toll exceeding 3 Million worldwide as of 28 April 2021. The pandemic highlighted the crucial role played by Information and Communication Technology in keeping businesses running and societies functional in times of lockdowns and quarantines. COVID-19 has accelerated our dependence on digital technologies and highlighted the life-saving benefits of connectivity. Some of the most important technologies and applications used to combat the Virus and mitigate its impacts are discussed in this article.Internet of Things (IoT):In the healthcare and medical services arena, Applications of IoT include: monitoring patients from a remote location, tracking medication orders, and using wearables to transmit health information to the concerned health care professionals. Several innovators, medical organizations, and government bodies are looking to utilize IoT tools in order to reduce the burden on the healthcare systems.Internet-connected thermometers, known as Smart Thermometers are used to screen people for high temperature.  These thermometers are linked to a mobile application, which allows them to transmit their readings to the medical center immediately. Once received, this data is assimilated to generate daily maps showing which regions are witnessing an increase in high fevers, thereby allowing authorities to identify potential hotspots.Telehealth is the practice of using IoT to facilitate remote patient monitoring, thus; allowing clinicians to evaluate, diagnose, and treat patients without needing any physical interaction with them. Adopting telehealth techniques lessened the burden on the overworked hospital staff, and has reduced the risk of spread of the virus from the infected individuals to the healthcare personnel. Several telemedicine tools were developed lately including Chatbots that can make initial diagnosis based on symptoms identified by patients, teleconsultation software, and portable medical tablets. However, the true potential of telemedicine can only be realized when existing telemedicine platforms are used in conjunction with other technologies such as drones, robots, smart wearables, and next-generation 5G cellular networks. China developed a smart phone app health rating system that is tracking millions of people daily. It assigns three colors to people (green, yellow, and red) on the basis of their travel and medical history. Only those who were assigned a green color could be allowed in public spheres.RoboticsRobots were on the front line to prevent the spread of Coronavirus. They served to spray disinfectants, prepare meals at hospitals, double up as waiters in restaurants, dispense hand synthesizers, and deliver food to those in quarantine. In many hospitals, robots were also performing diagnosis, conducting thermal imaging, and transporting medical samples. A hospital at Wuhan was being staffed entirely by robots. Most of the devices are IoT enabled and services are carried out by robots. The initial screening of the patients is done by 5G enabled thermometers that send instant updates. There are rings and bracelets that are connected to the AI platform so that it can monitor all changes in the body. In addition, it is suggested that a kind of ambulance robot, operated remotely and supplied with medical tools such as a smart thermometer, automatic external defibrillator, coronavirus test kit, and other instruments, could be used to instruct the public on appropriate actions to take in public spaces in an emergency. In hotels and restaurants, robots could carry luggage and guide guests through front desk services. Miscellaneous tasks such as cleaning rooms and pouring coffee were also done by robots. Robots, equipped with AI, can potentially provide information, do housekeeping work, provide food services, and help to comfort and entertain the customer in a safe way. Restaurants have also adopted robots to transfer goods from warehouses to trucks and customers amid the COVID-19 pandemic to limit potential virus contamination. At the time of risk of people-to-people contact, Autonomous Vehicles are proving to be of great utility in delivering essential goods like medicines and food items, and disinfecting hospitals. Electric street cleaning vehicles were also used at times of lockdown.Drone Technology:Drones can provide numerous benefits in managing the COVID-19 pandemic due to the minimized human interaction and the ability to reach otherwise inaccessible areas. Several countries around the world have joined forces with numerous researchers and innovators in an attempt to find ingenious ways of using drones to fight the COVID-19. Drones were transporting both medical equipment and patient samples, saving time and enhancing the speed of deliveries, while preventing contamination of medical samples. Agricultural drones were spraying disinfectants in the countryside. China employed the use of drones equipped with infrared cameras to carry out large-scale temperature measurements in several residential areas. Drones powered with facial recognition were also being used to broadcast warnings to the citizens not to step out of their homes, and chide them for not wearing face masks. In India, a ‘‘corona combat’’ drone, is equipped with a thermal camera for screening individuals, a night vision camera for monitoring the crowd, a portable medical box for carrying essential medical supplies, a loudspeaker for making announcements, and a disinfectant tank with a capacity of 10 liters for sanitizing public spaces.Artificial Intelligence:With the help of data analytics and predictive models, AI proved to be a highly effective tool against the COVID-19 Pandemic. Risk prediction is one of the important AI applications during the Pandemic. The risk of getting infected is a function of numerous factors where mathematical modeling would not yield fruitful results. However, a comprehensive analysis of these factors integrated with AI techniques, can offer a more precise and reliable prevision of individual risk profiles. Once a person is infected, AI capabilities can also be used to determine the probability of survival and the requirement of ICU treatment for COVID-19 patients. , AI techniques, particularly machine learning algorithms, can also be used to correlate the patient’s data parameters with a specific drug’s usage. In the medical diagnosis and screening arena, AI enhanced the tools of face scanners, medical imaging, and voice detection systems for rapid diagnosis. Machine Learning has proved its effectiveness in speeding up the process of drug development. Scientists are also using AI to help identifying existing drugs that can be beneficial in treating the COVID-19. For Virus modeling and analysis, Machine Learning happens to be one of the most effective tools. ML models can be used to compare the viral genome with known genomes and identify existing similarities. Other applications of AI include curbing the propagation of fake news and misinformation of social media platforms as well as enforcing the lockdown measures.5G TechnologyIn comparison to 4G, 5G is expected to have better performance in terms of higher speed, lower latency, wider range, increased availability, and more reliability. Together with other technologies like IoT and AI, 5G technology has the potential to revolutionize the healthcare sector. 5G can enable immersive virtual and augmented reality (VR/AR) applications, which can lead to an interactive experience in telemedicine, and equip medical teams to provide immediate expertise in regards to possible complications and treatment strategies. In China, 5G-enabled medical imaging platforms allowed for real-time diagnosis of COVID-19 patients, and in doing so, relieved some of the load on the hospital’s medical staff. . A 5G Infra-Red thermal imaging monitoring system can enable the real-time temperature of moving bodies with high accuracy and precision. The data accumulated by the systems can then be transmitted to the central monitoring system with ultra-low latency using 5G networks.ConclusionCOVID-19 has demonstrated the importance of digital readiness to allow life to continue –as much as possible- during pandemics. Supporting a digitized world and staying current in the latest technology will be essential for any country to remain competitive in a post COVID-19 world. Digitization and pandemics have accelerated changes to jobs available to humans. The pandemic has highlighted and exacerbated inequalities of all kinds, including the digital divide. Those without access to digital technology – almost half of the world – are denied opportunities to study, communicate, trade, work, and participate in much of what is now normal life for the richer half of the world.</p

Fabric based supercapacitors towards wearable applications

Nowadays, the constant need to obtain energy from renewable energies demands a high range of devices capable of storing energy. Comparing renewable energy to non-renew- able energy, the ability to store energy is very important due to the lack of continuity of en- ergy generation. The use of supercapacitors is a great opportunity to obtain a storage device capable of supplying small electronic devices with properties such as high flexibility and per- meability, which allow these components to be integrated in wearable technologies. Some supercapacitors were already developed, showing the potential to be used as en- ergy storage devices, using carbon yarns as electrodes and SSS as electrolyte, providing the desired properties for these devices to be used in wearable technologies. In this thesis re- search was conducted to study the potential of using commercial carbon yarns as a substrate to obtain electrodes with different active materials, for instance copper and copper iodide, to use in fiber-based supercapacitors. These materials were analyzed trough optical microscopy to understand the material's adhesion, Raman spectroscopy for elemental characterization, Cyclic voltammetry to obtain the electrochemical information needed to seek the potential of these samples, from both 3-electrode analysis (isolated electrode behavior) and 2-electrode setup to evaluate a fully constructed supercapacitor when subjected to different potential windows and scan-rates. The result of this thesis provides alternatives to the prepare electrodes for fiber-shaped supercapacitors towards wearable technologies, expanding the range of characteristic prop- erties and therefore, make these devices more desirable to use in this mean. Supercapacitor behavior was found using devices with both electrodes, even with some problems regarding electrode stability due to the irreversible reactions occurring during the potential sweep, hav- ing the electrode coating react with the electrolyte.A necessidade constante em utilizar energia obtida por vias renováveis na atualidade, exige uma exploração afincada em dispositivos capazes de armazenar essa energia. Compa- rando estas vias com vias não renováveis, a capacidade de armazená-la é muito importante devido à intermitência na geração dessa energia. Os supercondensadores são um ótimo meio de obter dispositivos de armazenamento capazes de alimentar pequenos dispositivos, man- tendo propriedades como uma alta flexibilidade e permeabilidade, que permitem estes equi- pamentos serem integrados em tecnologia wearable. Já foram desenvolvidos supercondensadores que utilizam fios de carbono como elétro- dos já foram desenvolvidos, e demonstram potencial a serem usados como dispositivos de armazenamento energia, oferecendo também as propriedades necessárias à sua integração em tecnologia wearable. Nesta tese, uma pesquisa foi feita com o objetivo de estudar o po- tencial o potencial em utilizar fios de carbono como substrato, para obter electrodos com di- ferentes materiais ativos, nomeadamente cobre e iodeto de cobre, para utilizar em supercon- densadores em fibras. Estes materiais foram caracterizados através de microscopia ótica de modo a avaliar a adesão e resistência mecânica, espectroscopia de RAMAN para caracterização elemental, e voltametria cíclica para obter as propriedades eletroquímicas destes elétrodos e identificar o potencial destes dispositivos, através de VC a 3 elétrodos (comportamento dos elétrodos isolados) e a 2 elétrodos (comportamento dos dispositivos constituídos por estes elétrodos quando submetidos a diferentes janelas de potencial e velocidades de varrimento de tensão). Esta tese oferece alternativas à escolha de elétrodos flexíveis para integração em super- condensadores em fibras, aumentando a gama de propriedades disponíveis, e assim tornar estes dispositivos mais atrativos à sua utilização. Foram obtidos problemas nos supercondensadores obtidos, devido á reatividade dos elétrodos com o eletrólito durante os testes eletroquímicos, e às reações irreversíveis que provoca

A new system to detect coronavirus social distance violation

In this paper, a novel solution to avoid new infections is presented. Instead of tracing users’ locations, the presence of individuals is detected by analysing the voices, and people’s faces are detected by the camera. To do this, two different Android applications were implemented. The first one uses the camera to detect people’s faces whenever the user answers or performs a phone call. Firebase Platform will be used to detect faces captured by the camera and determine its size and estimate their distance to the phone terminal. The second application uses voice biometrics to differentiate the users’ voice from unknown speakers and creates a neural network model based on 5 samples of the user’s voice. This feature will only be activated whenever the user is surfing the Internet or using other applications to prevent undesired contacts. Currently, the patient’s tracking is performed by geolocation or by using Bluetooth connection. Although face detection and voice recognition are existing methods, this paper aims to use them and integrate both in a single device. Our application cannot violate privacy since it does not save the data used to carry out the detection and does not associate this data to people