It generates an abundance of data that requires processing and analytical power to produce valuable insights regarding health and business.
Today, we are witnessing how health monitoring, pharmacy, hospital management, and diagnostics have started to rely on IoT support. Its precision and time-saving nature make IoT critical for medicine.
Meanwhile, ongoing cost reductions for electronic components creates an opportunity for bold experiments in the medical field. It seems like IoT has firmly entrenched itself in the healthcare industry for the foreseeable future.
Real-world IoT-based apps are far from being just all-round connectivity tools but are a convergence of technologies balanced for optimal industry deliverables. In fact, it’s impossible or meaningless to implement AI, Machine Learning, Cloud Computing, and other concepts circulating over healthcare without a robust IoT foundation.
That’s why IoT needs to be the core of Smart Healthcare and why PSA, among many other companies, focuses on IoT in healthcare - providing robust integration with cutting-edge technologies to uncover opportunities we never experienced before.
IoT in Healthcare Today
Speed of decision-making coupled with the precision of medical reports remains the primary direction for IoT in healthcare developments. The latest research reveals a keen interest among the medical community in IoT-related developments.
For example, a close look at data reveals high hopes for IoT in terms of diagnostics, telemedicine, and advanced operational processes within smart hospitals. We have every reason to believe that IoT will become more than a medical assistant, rather it will become a full-fledged decision-maker to address medical challenges. Moreover, excessive analytics will allow the focus to shift from the emergency ambulance and after-the-fact visits to predictive medical help.
However, healthcare authorities and institutes shouldn’t be the only target for IoT in healthcare developments. IoT can also unleash opportunities for patients to self-manage their treatment.
Research suggests that more than half of smartphone users have installed heath-tracking apps while 300m+ downloads of such apps are detected annually. More targeted and precise wearables together with more versatile analytics about an individual’s health will help to reduce the pressure on medical facilities and improve the overall statistics in terms of recovery.
Balancing Computing Power within IoT in Healthcare
The ever-growing demand for smart management of medical data and real-time clinical assistance has resulted in intense interest in both cloud and edge computing when it comes to healthcare.
The surge in edge computing capacities will promote complex AI applications to be deployed near the source of data generation to deliver more analytical insights in real-time. For healthcare, it’s already unlocked body position and movement monitoring with deviation alarm, rapid screening, AI-supported surgery tools for minimised invasion, smart video stream analysis during surgery, DNA sequencing in real-time, and many more applications.
A reduction in latency makes real-time edge apps more reliable within hospital settings where substantial data needs to be processed simultaneously. Thus, by focusing on hardware with multiple connectivity opportunities, the foundations for integrated smart healthcare systems are being laid.
Cloud is being adopted as a platform for the end-to-end management of the varied and sensitive data that’s produced daily by any medical facility. Thanks to its flexibility and scalability it can alleviate the challenges of the increasing complexity of IoT in healthcare systems caused by incremental edge adoption as well.
Cloud is suitable for storing and processing large amounts of operational, financial, patient, and drug data providing ongoing cost estimation, scheduling, and inventory management with data backups and convenient access from any site.
Today, when strategic planning is highly prioritised, the healthcare sector reveals a tangible demand for integrated systems with balanced computing capabilities to address comprehensive industry challenges. For instance, smart health monitoring systems can leverage more edge capacities to automate drug delivery or bed adjustment when indicating health deviations, while cloud reflects data in medical history and analyses it after to perform health forecasts.
Key trends regarding Cloud-Edge include:
Edge + Cloud hybrid for maximised efficiency with distributing workloads and coherence between distributed assets. Such a trend will see the cloud become an overall management centre for increased transparency and will improve controllability in case of an asset failure.
5G for maximized throughput within time-critical applications for heavy data transfer. 5G allows for the connection of many more devices than 4G or LTE while decreasing energy consumption. The enhanced connectivity also enables cloud management of MEC (multi-access edge computing) applications.
Strengthened authentication measures, such as network segmentation, full-duplex authentication integration, and regular updates are vital to protect sensitive data. As edge infrastructures are more secure by default, it’s better to avoid the transition of redundant data in the cloud.
A thought-out approach to balancing computing capacities allows healthcare organisations and authorities to develop optimised strategies for maintaining data confidentiality, failure resistance, and highest efficiency, and create new models for patient care.
Neural Networks Adoption for Diagnostics Assistance
When it comes to diagnostics where the quality of the results is a priority, the combination of IoT and AI outputs the most impressive results.
One example is the management of visual analysis. For instance, proven DL methods provide chest disease identification at an accuracy of 98% by analysing X-rays. The same is true of CT scans that can be successfully analysed for the presence of brain tumours.
Recent research has found that a neural network (NN) can identify melanoma 10% more accurately than a medical expert. Thus, deep learning models effectively interpret medical shots by combining multiple aspects of visualisation, such as the size, volume, and shape of the tissue.
Likewise, NN analyses multiple types of data, and identifies, for instance, the risk of heart attacks or voice pathology.
The scope of the application is only expanding, and its true potential lies in ever more complicated analytical applications to consider more factors for current state and risk estimation, profound diagnostics, and error identification in previous diagnoses.
Symptoms, complaints, medical history, and current tests combined for IoT analysis can deliver groundbreaking opportunities for autonomous diagnostics. Potentially, accurate diagnostics and forecasts could help healthcare systems save billions of pounds that’s currently spent on unnecessary medical care, interventions, and medical mistakes.
Beyond Traditional Monitoring of Vital Signs
IoT-based systems reveal opportunities for augmented patient monitoring in order to detect dangerous states. The combination of real-time vital sign monitoring, environmental data collection, and patient health history within one analytical tool will allow for instant and accurate detection of any suspicious state for a particular patient, as well as prescribing personalised medical treatment.
IoT in healthcare also promotes total transparency and real-time control, which allows for remote health monitoring both for hospital and in-home supervision. IoT-based tools possess comprehensive data and analytical capabilities, which could help to eliminate unnecessary visits to health facilities. At the same time, they can promote medical visits in advance before the disease turns into an acute form.
All the interested stakeholders (physicians, insurance agents) can be provided with access to such data. Generally, IoT allows turning the healthcare paradigm from ambulance-focused help to predictive treatment, thus significantly unloading medical facilities.
Promoting IoT in Healthcare Today
Healthcare is adapting to and striving to make the IoT. To make the IoT journey as beneficial as possible, the following should be considered:
Think strategically. Coherent full-fledged systems for comprehensive manageability of distributed units are what IoT in healthcare is headed towards. So, any development should be performed with interoperability and versatile connectivity in mind.
Focus on quality and accuracy. Next-gen analytics needs to embrace data from various sources utilising the latest achievements in neural network development to provide a valuable tool for monitoring, diagnostics, and health forecasts.
Think out the edge infrastructure to enable various medical scenarios in real-time to precisely meet the target set.
Promote accessibility and transparency for remote patient care and treatment by developing cloud infrastructures.
Real-time access and ongoing monitoring will be the basis of the new reality for healthcare.
Author details: Julia Seredovich is Business Operations Manager at PSA
