Contemplate on Internet of Things Transforming as Medical Devices - The Internet of Medical Things (IOMT)

2019 ◽  
Author(s):  
V. PremaLatha ◽  
E. Sreedevi ◽  
S. Sivakumar
Keyword(s):  
Internet Of Things ◽  
Medical Devices ◽  
The Internet ◽  
Internet Of Medical Things

scholarly journals An energy-efficient fog-to-cloud Internet of Medical Things architecture

2019 ◽  
Vol 15 (5) ◽  
pp. 155014771985197 ◽  
Author(s):  
Sabeen Tahir ◽  
Sheikh Tahir Bakhsh ◽  
Maysoon Abulkhair ◽  
Madini O Alassafi
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Medical Devices ◽  
Energy Efficient ◽  
Low Cost ◽  
Vital Role ◽  
The Internet ◽  
Implanted Medical Devices ◽  
Internet Of Medical Things ◽  
The Internet Of Things

In order to increase the reliability, accuracy, and efficiency in the eHealth, Internet of Medical Things is playing a vital role. Current development in telemedicine and the Internet of Things have delivered efficient and low-cost medical devices. The Internet of Medical Things architectures being developed do not completely recognize the potential of Internet of Things. The Internet of Medical Things sensor devices have limited computation power; in case if a patient is using implanted medical devices, it is not easy to recharge or replace the devices immediately. Biosensors are small devices with limited energy if these devices do not wisely utilize the energy may drain sharply and devices become inactive. The current medical solutions place the bulk of data on cloud-based systems that ultimately creates a bottleneck. In this article, an energy-efficient fog-to-cloud Internet of Medical Things architecture is proposed to optimize energy consumption. In the proposed architecture, Bluetooth enabled biosensors are used, because Bluetooth technology is an energy efficient and also helps to enable the sleep and awake modes. The proposed fog-to-cloud Internet of Medical Things works in three different modes periodic, sleep–awake, and continue to optimize the energy consumption. The proposed technique enabled the sensing modes that gathers the patients’ data efficiently based on their health conditions. The sensed data are transmitted to the relevant fog and cloud devices for further processing. The performance of fog-to-cloud Internet of Medical Things is evaluated through simulation; the results are compared with the results of existing techniques in terms of an end-to-end delay, throughput, and energy consumption. It is analyzed that the proposed technique reduces the energy consumption between 30% and 40%.

scholarly journals Medical Device Integration Model Based on the Internet of Things

2015 ◽  
Vol 9 (1) ◽  
pp. 256-261 ◽  
Author(s):  
Aiyu Hao ◽  
Ling Wang
Keyword(s):  
Information System ◽  
Internet Of Things ◽  
Medical Device ◽  
Medical Devices ◽  
Medical Information ◽  
Medical Information System ◽  
The Internet ◽  
Model Based ◽  
Device Integration ◽  
The Internet Of Things

At present, hospitals in our country have basically established the HIS system, which manages registration, treatment, and charge, among many others, of patients. During treatment, patients need to use medical devices repeatedly to acquire all sorts of inspection data. Currently, the output data of the medical devices are often manually input into information system, which is easy to get wrong or easy to cause mismatches between inspection reports and patients. For some small hospitals of which information construction is still relatively weak, the information generated by the devices is still presented in the form of paper reports. When doctors or patients want to have access to the data at a given time again, they can only look at the paper files. Data integration between medical devices has long been a difficult problem for the medical information system, because the data from medical devices lack mandatory unified global standards and have outstanding heterogeneity of devices. In order to protect their own interests, manufacturers use special protocols, etc., thus causing medical devices to still be the "lonely island" of hospital information system. Besides, unfocused application of the data will lead to failure to achieve a reasonable distribution of medical resources. With the deepening of IT construction in hospitals, medical information systems will be bound to develop toward mobile applications, intelligent analysis, and interconnection and interworking, on the premise that there is an effective medical device integration (MDI) technology. To this end, this paper presents a MDI model based on the Internet of Things (IoT). Through abstract classification, this model is able to extract the common characteristics of the devices, resolve the heterogeneous differences between them, and employ a unified protocol to integrate data between devices. And by the IoT technology, it realizes interconnection network of devices and conducts associate matching between the data and the inspection with the terminal device in a timely manner.

scholarly journals A Review on Data Securing Techniques using Internet of Medical Things

2021 ◽  
Vol 3 (3) ◽  
pp. 150-163
Author(s):  
P. P. Joby
Keyword(s):  
Older People ◽  
Basic Principle ◽  
Medical Devices ◽  
Data Security ◽  
Critical Factor ◽  
The Internet ◽  
Major Goal ◽  
Internet Of Medical Things ◽  
Machine To Machine Communication ◽  
Machine Communication

At present, the traditional healthcare system is completely replaced by the revolutionary technique, the Internet of Medical Things (IoMT). Internet of Medical Things is the IoT hub that comprises of medical devices and applications which are interconnected through online computer networks. The basic principle of IoMT is machine-to-machine communication that takes place online. The major goal of IoMT is to reduce frequent or unwanted visits to the hospitals which makes it comfortable and is also highly preferred by the older people. Another advantage of this methodology is that the interpreted or collected data is stored in cloud modules unlike amazon and Mhealth, making it accessible remotely. Although there are countless advantages in IoMT, the critical factor lies in data security or encryption. A surplus number of threat related to devices, connectivity, and cloud might occur under unforeseen or threatening circumstances which makes the person in the situation helpless. Yet, with the help of data security techniques designed especially for Internet of Medical Things, it is possible to address these challenges. In this paper, a review on data securing techniques for the internet of medical things is made along with a discussion on related concepts.

scholarly journals Prototype Sistem Monitoring Infus Berbasis IoT (Internet of Things)

2020 ◽  
Vol 4 (2) ◽  
pp. 155-163
Author(s):  
Taufik Akbar ◽  
◽  
Indra Gunawan ◽  
Keyword(s):  
Internet Of Things ◽  
Medical Devices ◽  
Science And Technology ◽  
Medical Science ◽  
The Internet ◽  
Patient Room ◽  
The World ◽  
Weight Sensor ◽  
The Internet Of Things ◽  
Control Infusion

The development of increasingly sophisticated medical science and technology has an impact on the development of science and technology in the field of medical-devices. One of the existing equipment and is often used in hospitals, one of which is an IV. Currently in the world of health, infusion is still controlled manually. Because it takes time if the nurse has to go back and forth throughout the patient room. Not only is it time consuming, but there will be risks if it is too late to treat a patient whose infusion has run out. Technology needs to be used to minimize risks in the medical world, one of which is the application of IoT technology. This study aims to make it easier for nurses to control infusion conditions in real time using the concept of IoT ( the Internet of Things). The method used is the Waterfall method. This research uses hardware consisting of Load Cell with the HX711 module as a weight sensor, NodeMCU V3 as a processor, and Thingspeak Web server as the interface with the user. The results of the measurement of the tool made have an error of 0.25 Gram, sending data to the Thingspeak.com Server requires a good connection for maximum results.

scholarly journals FIViz: Forensics Investigation through Visualization for Malware in Internet of Things

2020 ◽  
Vol 12 (18) ◽  
pp. 7262
Author(s):  
Israr Ahmad ◽  
Munam Ali Shah ◽  
Hasan Ali Khattak ◽  
Zoobia Ameer ◽  
Murad Khan ◽  
...  
Keyword(s):  
Decision Support ◽  
Internet Of Things ◽  
Decision Support Systems ◽  
Support Systems ◽  
Smart Cities ◽  
Security And Privacy ◽  
The Internet ◽  
Data Set ◽  
Raw Data ◽  
Internet Of Medical Things

Adoption of the Internet of Things for the realization of smart cities in various domains has been pushed by the advancements in Information Communication and Technology. Transportation, power delivery, environmental monitoring, and medical applications are among the front runners when it comes to leveraging the benefits of IoT for improving services through modern decision support systems. Though with the enormous usage of the Internet of Medical Things, security and privacy become intrinsic issues, thus adversaries can exploit these devices or information on these devices for malicious intents. These devices generate and log large and complex raw data which are used by decision support systems to provide better care to patients. Investigation of these enormous and complicated data from a victim’s device is a daunting and time-consuming task for an investigator. Different feature-based frameworks have been proposed to resolve this problem to detect early and effectively the access logs to better assess the event. But the problem with the existing approaches is that it forces the investigator to manually comb through collected data which can contain a huge amount of irrelevant data. These data are provided normally in textual form to the investigators which are too time-consuming for the investigations even if they can utilize machine learning or natural language processing techniques. In this paper, we proposed a visualization-based approach to tackle the problem of investigating large and complex raw data sets from the Internet of Medical Things. Our contribution in this work is twofold. Firstly, we create a data set through a dynamic behavioral analysis of 400 malware samples. Secondly, the resultant and reduced data set were then visualized most feasibly. This is to investigate an incident easily. The experimental results show that an investigator can investigate large amounts of data in an easy and time-efficient manner through the effective use of visualization techniques.

scholarly journals Improved Proportional Fair Algorithm for Transportation of 5G Signals in Internet of Medical Things

2020 ◽  
Vol 9 (2) ◽  
pp. 1810-1814
Keyword(s):  
Internet Of Things ◽  
Performance Metrics ◽  
Path Loss ◽  
Data Rate ◽  
Hybrid Network ◽  
The Internet ◽  
Battery Life ◽  
Proportional Fair ◽  
Internet Of Medical Things ◽  
Medical Healthcare

The Internet of medical things (IoMT) is a hybrid network inwhich numerous technologies like Bluetooth, Wi-Fi, and Cellular technology are integrated on a single platform. The internet of things applied to the medical healthcare necessitates enormous data rate and tremendous bandwidth along with better battery life with reliable and versatile connectivity. The use of 5G network satisfies these prerequisite with its tremendous data rate capabilities and assists human health services diagnosis and treatment. In this paper, improved proportional fair algorithm is introduced and is compared with existing scheduling algorithm for developing revolutionary changes in the medical healthcare.5G networks represent a contemporary approach which encounter a hybrid digital network for developing Internet of things. Performance metrics considered for simulation studies are throughput, path-loss and SNR

scholarly journals Internet of Things and Healthcare Technologies: A Valuable Synergy from Design to Implementation

2018 ◽  
Vol 2 (3) ◽  
pp. 128-142
Author(s):  
Kalpna Gautam ◽  
Vikram Puri ◽  
Jolanda G Tromp ◽  
Chung Van Le ◽  
Nhu Gia Nguyen
Keyword(s):  
Internet Of Things ◽  
Research And Development ◽  
The Internet ◽  
The Future ◽  
Software Platforms ◽  
Healthcare Technologies ◽  
Internet Of Medical Things ◽  
Human Healthcare

Internet of Things (IoT) promises to be a reliable technology for the future. Healthcare is one of the fields which are rapidly developing new solutions. The synergy between IoT and healthcare promises to be very beneficial for human healthcare and evolved into a new field of research and development: the Internet of Medical Things (IoMT). This paper presents a review on various enabling IoMT technologies based on the latest publications and technology available in the marketplace. This article also analyzes the various software platforms available in the field of IoMT and the current challenges faced by the industry

scholarly journals IMPACT OF AI IN INTERNET OF MEDICAL THINGS FOR HEALTH CARE DELIVERY

2021 ◽  
Vol 8 (8) ◽  
pp. 18-26
Author(s):  
NEETA NATHANI ◽  
Zohaib Hasan
Keyword(s):  
Health Care ◽  
Internet Of Things ◽  
Health Care Delivery ◽  
Care Delivery ◽  
Integrated Approach ◽  
Health Service Delivery ◽  
The Internet ◽  
Public Health Services ◽  
Internet Of Medical Things ◽  
The Internet Of Things

The Internet of Things (IoT) is a network of wireless, interconnected, and networked digital devices that can gather, send, and store data without the need for human or computer interaction. The Internet of Things has a lot of promise for expediting and improving health care delivery by proactively predicting health issues and diagnosing, treating, and monitoring patients both in and out of the hospital. Understanding how established and emerging IoT technologies may help health systems deliver safe and effective treatment is becoming increasingly critical. The purpose of this viewpoint paper is to present an overview of existing IoT technology in health care, as well as to describe how IoT devices are improving health service delivery and how IoT technology can alter and disrupt global healthcare in the next decade. The promise of IoT-based health care is explored further to theorize how IoT can increase access to preventative public health services and help us migrate from our existing secondary and tertiary health care systems to a more proactive, continuous, and integrated approach. The intersection of the Internet of Medical Things (IoMT) for patient monitoring and chronic care management and the use of Artificial Intelligence (AI) is becoming more promising than ever as the adoption of telemedicine continues to grow dramatically. Connected devices generate huge volumes of data based on real-time measurements of patient vitals, which is delivered to cloud-based applications that are monitored by medical specialists in virtual contact centres. The policy is applied per-patient, and healthcare providers receive warnings and messages when a patient's heart rate, oxygen level, glucose level, blood pressure, or other measurement reaches a set threshold. Depending on the sort of telemedicine and telehealth platforms in use, this data is tracked and acted upon by specialists who monitor many patients for many different practices, and in other circumstances, this data is sent directly to the provider. AI in healthcare, as well as other crucial technologies are essential for resolving the issue and producing future prosperity.

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