Application of IoT in Virus Detection

Version	Summary	Created by	Modification	Content Size	Created at	Operation
1		Christos L. Stergiou	--	1960	2024-03-10 00:18:33	\|
2	Reference format revised.	Lindsay Dong	-67 word(s)	1893	2024-03-11 03:07:59	\|

This entry is adapted from the peer-reviewed paper 10.3390/app14010120

Today, healthcare system models should have high accuracy and sensitivity so that patients do not have a misdiagnosis. For this reason, sufficient knowledge of the area is required, with the medical staff being able to validate the correctness of their decisions. Therefore, artificial intelligence (AI) in combination with other emerging technologies could provide many benefits in the medical sector.

IoT healthcare systems virus

1. Introduction

It appears that there is a pressing need to incorporate new technologies into medical care for the best possible detection of such viruses. Five cutting-edge technologies—Internet of Things (IoT), Wireless Sensor Networks (WSN), Cloud Computing (CC), Machine Learning (ML), and Wireless Networks—can be utilized in conjunction to combat viruses and the threat of infectious illnesses. All these technologies can be worked under the broad term of Internet of Medical Things (IoMT), which is the IoT that has reconstructed hospital settings and invented a new paradigm. Additionally, it offers numerous opportunities, due to the wearable devices used by plenty of people, to enhance health and well-being associated with eHealth and mHealth ^[1]. WSN takes advantage of features such as low cost, availability, and accessibility, and as a result, there has been an increase in the adoption of these mobile sensors. Additionally, these personalized healthcare systems gather pertinent biophysical data to aid in medical diagnoses and decisions, and they could be stored, maintained, and processed in the cloud ^[2].

Moreover, IoT-based Big Data (BD) and ML can offer a handful of opportunities for healthcare systems relying on IoT, and therefore the new term of Artificial Intelligence of Things (AIoT). WSN systems’ real-time health data can be utilized to assist patients with self-administered treatments. Furthermore, mobile devices with mobile applications are frequently used and integrated with the terms of telemedicine and mHealth through the IoMT. The results of medical data analytics from data analysis platforms established on the cloud increase the applicability of data interpretations and reduce the time of analyzing data outputs and, thus, the detection and prediction of viruses and diseases.

2. Limitations Could Be Addressed by IoT

Conventional medical methods have been effective in treating various health conditions, but they do have some limitations and barriers that can be addressed by integrating the Internet of Things (IoT) and related technologies ^[3]^[4]^[5]. Some of these limitations and how the IoT can help overcome them are ^[6]^[7]:

Limited monitoring: Conventional medical methods often involve periodic visits to healthcare facilities, which can lead to limited monitoring of patients’ health conditions. IoT-enabled devices, such as wearable health trackers and remote patient monitoring systems, offer continuous and real-time health data collection, providing healthcare professionals with a more comprehensive view of patients’ health statuses.

Inefficient data collection: The manual recording of patient information used in traditional data-gathering techniques in the healthcare industry can be time-consuming and prone to inaccuracy. By automating data gathering procedures, IoT technologies lower the possibility of human error and facilitate quicker access to vital health data.

Lack of personalization: Conventional medical practices frequently rely on generic methods that may not adequately address the needs of each patient. By evaluating a patient’s real-time data, the IoT can enable personalized medicine by allowing healthcare professionals to customize interventions and treatments depending on particular health problems and response patterns.

Limited access to healthcare in remote areas: There are many localities with poor access to healthcare facilities, particularly in rural or outlying areas. By enabling virtual consultations, remote diagnostics, and ongoing monitoring, IoT-enabled telemedicine and remote healthcare systems help close this gap, enhancing healthcare access and results in underserved areas.

Delayed diagnosis and intervention: Particularly in the case of chronic illnesses, traditional healthcare approaches may result in delayed diagnosis and action. IoT-based remote monitoring enables early abnormality detection, prompt response, and the avoidance of potential health emergencies.

Fragmented healthcare systems: Traditional medical practices frequently use disjointed data storage and communication platforms, which makes it difficult to access thorough patient records. Using IoT technologies, a more interconnected and unified healthcare system may be created by combining data from many sources and devices.

Patient compliance and adherence: It might be difficult to monitor and enforce patient adherence to recommended therapies and pharmaceutical regimens. IoT gadgets can deliver alerts, monitor medicine intake, and give behavioral cues, encouraging patients to follow their treatment regimens.

Limited data for research and analysis: For medical research and analysis, traditional medical practices might only supply partial data. Big data analytics, medical research, and the creation of prognostic models for illness prevention and treatment are all greatly facilitated by IoT-generated data.

Data security and privacy concerns: IoT use in healthcare sparks worries about patient privacy and data security. Strong data encryption, secure communication methods, and adherence to pertinent data protection laws like HIPAA and GDPR are all necessary for addressing these issues.

Healthcare may overcome these restrictions and obstacles by utilizing the IoT and related technologies, which will result in better patient outcomes, improved disease management, and more effective healthcare delivery. When implementing IoT solutions in the healthcare industry, it is crucial to solve issues with data protection, interoperability, and scalability.

3. Technological Challenges in Microbiology Addressed by IoT

IoT (Internet of Things) and associated technologies can be very helpful in addressing several technological issues in the microbiology sector. The study of microorganisms, such as bacteria, viruses, fungi, and other tiny organisms, is known as microbiology ^[3]^[6]^[8]. The IoT can assist in overcoming the following technological issues in microbiology ^[5]^[7]:

Real-time monitoring of microbial growth: Traditional techniques for keeping track of microbial development in cultures can be labor-intensive and time-consuming. Researchers can remotely monitor and control environmental conditions thanks to the ability of IoT-enabled sensors to offer real-time data on variables like temperature, pH, and oxygen levels.

Remote data collection from field samples: It can be logistically difficult to gather field samples for microbiological investigation and transfer them to the lab. Researchers may track microbial activity on-site using IoT-based remote sensing devices to collect data from varied environments and communicate it instantaneously to labs.

Data-intensive microbiome analysis: Microbiome analysis, which examines microbial communities and their interactions throughout various ecosystems, produces significant data. High-throughput sequencing technology and IoT-based sensors can speed up data gathering and processing, which will improve our understanding of complex microbiomes.

Early detection of infectious diseases: For the sake of public health, rapid and early detection of infectious diseases is essential. IoT devices can identify specific microbiological indicators, facilitating quicker diagnosis and intervention. Examples include wearable biosensors and point-of-care diagnostic tools.

Environmental monitoring for outbreaks: It might be difficult to monitor environmental conditions that cause illness epidemics, like air pollution and water quality. In order to identify potential outbreak hazards, the IoT sensors may continuously monitor these elements and give real-time data.

Laboratory automation and efficiency: Microbiology laboratory processes can be labor and time-intensive. Lab automation and IoT-connected hardware can automate sample processing, data collection, and analysis, increasing accuracy and efficiency.

Remote collaboration and data sharing: The requirement for physical presence in the lab can make it difficult for researchers to work together on microbiology projects in various places. The IoT technologies make it possible for researchers to access and exchange data online, facilitating remote collaboration securely.

Patient monitoring and management: In medical microbiology, it is important to keep an eye on individuals who have infections. IoT devices can help with ongoing patient monitoring by sending information to healthcare professionals regarding infection signs, the efficacy of treatments, and the progression of recovery.

Antibiotic resistance surveillance: Antibiotic resistance is being tracked and addressed, which is a challenge for world health. Real-time monitoring of antimicrobial use and resistance patterns by IoT-enabled equipment can help with surveillance and well-informed decision-making.

Quality control in the food and beverage industry: Testing is required frequently to ensure microbiological safety in the manufacturing of food and beverages. IoT sensors can monitor important parameters like temperature and cleanliness, preventing contamination and preserving product quality.

Data security and privacy: Strong security measures are needed while handling sensitive microbiological data to prevent unwanted access or data breaches. Encryption, secure communication protocols, and adherence to pertinent data protection laws should all be used in IoT solutions.

IoT and associated technologies, which allow real-time data collecting, automation, remote monitoring, and improved collaboration, present intriguing answers to these problems. However, data integrity, validation of IoT-generated data, and efficient integration with current laboratory operations should all be taken into account when implementing the IoT in microbiology.

4. IoT in Healthcare Application Fields

IoT and other new technologies have a variety of uses in the healthcare industry that have the potential to completely change how care is delivered ^[3]^[6]. The following are some important application areas where these technologies can have a big impact ^[5]^[7]:

Remote patient monitoring: IoT devices allow for real-time data transmission to the cloud and continuous monitoring of a patient’s vital signs and health parameters. This is especially helpful for older patients, post-operative treatment, and controlling chronic illnesses.

Telemedicine and virtual health: IoT-driven telemedicine technologies make it easier to schedule follow-up appointments, remote diagnostics, and virtual consultations while maintaining data security.

Personalized medicine: IoT devices gather patient-specific health data, which, when combined with cloud-based analytics, allows healthcare practitioners to customize interventions and treatments based on the needs of individual patients.

Disease management and prevention: IoT devices can help manage treatment regimens and track the evolution of diseases. Anomalies that are discovered early can assist in averting complications and advance preventive healthcare.

Pharmaceutical research and manufacturing: IoT sensors improve quality control and regulatory compliance while ensuring ideal circumstances for medication development and manufacture.

Clinical trials: The use of IoT devices increases the dependability of trial results and ensures the security of sensitive patient data by collecting precise, ongoing data from trial participants.

Elderly care: Senior living facilities that use IoT-based monitoring systems encourage resident safety and well-being while securely storing data in the cloud for caregiver access.

Health and wellness wearables: IoT devices monitor physical activity, sleep habits, and general well-being, enabling people to actively control their health.

Emergency response and disaster management: IoT-enabled medical equipment enables healthcare professionals to remotely assess patient conditions during emergencies and natural catastrophes, facilitating quick response.

Public health surveillance: IoT data gathering and analytics help to monitor population health trends, track disease outbreaks, and create efficient public health interventions.

Data-driven decision-making: When paired with cloud-based analytics and artificial intelligence, IoT-generated data helps healthcare managers and providers make decisions based on the best available evidence.

Healthcare facility management: IoT sensors track the health of medical equipment, the environment, and patient flow, enhancing both operational effectiveness and patient care.

Precision agriculture and nutrition: IoT devices keep an eye on crop health and soil conditions to help produce foods that are nutrient-rich and encourage preventive healthcare.

Medical imaging and diagnostics: Medical imaging equipment that is IoT-connected streamlines data collection and transfer, increasing the precision and speed of diagnostic procedures.

Medical supply chain management: IoT sensors in the supply chain monitor the state of the equipment and medicines to ensure quality and avoid shortages.

Medical training and simulation: Medical education and skill development are improved by IoT-driven simulation systems that provide realistic training experiences.

Data privacy and security: Blockchain and other emerging technologies can improve the security and privacy of patient data, guaranteeing compliance with rules like HIPAA and GDPR.

IoT, emerging technologies, and secure cloud-based solutions have the power to revolutionize healthcare delivery, enhance patient outcomes, increase operational effectiveness, and spur innovation across a range of healthcare-related industries.

References

Oniani, S.; Marques, G.; Barnovi, S.; Pires, I.M.; Bhoi, A.K. Artificial Intelligence for Internet of Things and Enhanced Medical Systems. In Bio-Inspired Neurocomputing. Studies in Computational Intelligence; Springer: Singapore, 2020; Volume 903, pp. 43–59.
Stergiou, C.L.; Psannis, K.E.; Gupta, B.B. InFeMo: Flexible Big Data Management Through a Federated Cloud System. ACM Trans. Internet Technol. 2022, 22, 46.
Shreya, S.; Chatterjee, K.; Singh, A. A smart secure healthcare monitoring system with Internet of Medical Things. Comput. Electr. Eng. 2022, 101, 107969.
Butpheng, C.; Yeh, K.-H.; Hou, J.-L. A Secure IoT and Cloud Computing-Enabled e-Health Management System. Secur. Commun. Netw. 2022, 2022, 300253.
Tang, Z. A Preliminary Study on Data Security Technology in Big Data Cloud Computing Environment. In Proceedings of the International Conference on Big Data & Artificial Intelligence & Software Engineering (ICBASE), Bangkok, Thailand, 30 October–1 November 2020.
Ogiela, L.; Castiglione, A.; Gupta, B.B.; Agrawal, D.P. IoT-based health monitoring system to handle pandemic diseases using estimated computing. Neural Comput. Appl. 2023, 35, 13709–13710.
Butpheng, C.; Yeh, K.-H.; Xiong, H. Security and Privacy in IoT-Cloud-Based e-Health Systems—A Comprehensive Review. Symmetry 2020, 12, 1191.
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Subjects: Computer Science, Information Systems; Others

Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :

Christos L. Stergiou

Andreas P. Plageras

Vasileios A. Memos

Maria P. Koidou

Konstantinos E. Psannis

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Update Date: 11 Mar 2024

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