In the connected world - according to Gartner, there will be over 20 billion connected devices globally by 2020 - the Internet of Things is increasingly impacting every facet of our lives, both professional and personal. Take healthcare for instance. The proliferation of connectivity among both medical and personal health tracking devices is leading to an explosion in the amount of data generated. This in turn is opening up new possibilities for device manufacturers to embed Artificial Intelligence into their equipment. Medical devices, personal health and fitness trackers collect terabytes of data every day - monitoring factors such as our heart rate, steps, calories burned and blood pressure - most of which goes unused. However, the application of advanced analytics and AI on healthcare data has far reaching implications on the industry overall, a topic that I've been discussing at length in Düsseldorf this week at Medica 2016 - a global forum for the medical industry.
As the number of connected devices and resultant data generated continues to grow exponentially, manufacturers are looking to new methods to process these huge volumes of information. Traditionally, this data has been processed in the cloud, but as the volume has increased, so too has the challenge of shifting it all to a remote server, analysing it and returning the actionable information back to the device. Cloud computing is suitable for infrequent data transfer - much like the way the average consumer may use DropBox or Flickr for instance, to upload files occasionally. It is not as suitable for real-time insight and data processing; which is why new methodologies, such as edge computing, are coming to the fore.
The rise of edge computing
The relentless pace of technological development means that many devices now have the computational power to process more data themselves and adapt their performance accordingly. This is based on one of the multitude of sensors on a device generating data, which is subsequently run through a complex series of algorithms to be processed. These algorithms can make predictions about the device and then recommendations to improve its performance; otherwise known as embedded intelligence.
Using edge computing, only the most insightful, actionable data is shipped to the cloud, freeing up a huge amount of capacity and improving efficiencies as a result. Without having to process endless reams of largely unusable data, equipment vendors can use edge computing to crunch the most meaningful information and apply the intelligence accrued to enhance device development, resulting in better quality of patient care in turn.
Shifting to the edge
To take advantage of this shift, equipment manufacturers need to create the right conditions for their product development, by reengineering their design processes. Here are my six guiding principles for designing connected medical equipment that supports embedded intelligence.
- Software-defined - Most of the manual functionality we had in medical devices previously - switches, buttons and dials, for instance - are now being replaced with software. Why? Because software-defined devices require less maintenance, enabling routine checks and updates to be undertaken quickly for minimal outlay. Software updates, for instance, can be completed remotely to alter the functionality of the device or add new features.
- Autonomy - We can make systems automonous by incorporating remote monitoring and self learning capabilities. By introducing as much autonomy to each individual subsystem as possible, medical devices will be able to monitor themselves and self-heal if they develop any problems, removing the need for any manual intervention by the user.
- Efficiency - Improving the performance and efficiency of products in an aesthetic way has been one of key drivers for product designers for some time now. We're now able to take it a step further by using the capabilities afforded by Internet of Things and Artificial Intelligence. While the IoT allows us to generate the right data from the systems, AI can be used to make sense out of that data and generate actionable insights. Incorporating these capabilities into the design process is the first step towards building intelligent medical equipment. With efficiency gains derived from IoT and AI-driven design modifications, manufacturers can extend the uptime on production, creating equipment that can quickly take a new shape or direction if necessary, and connect to the wider system.
- Monitor and report - Every system and subsystem needs to have some form of monitoring while it is in the field, whether it be a heart monitor, MRI machine or fitness tracker. This enables each device or application to report back to the equipment vendor on its performance levels in the field, and in response helps them to redesign, or make any improvements or fixes where necessary. This also creates scope for interoperability between devices, which is critical to the further development of wider medical Internet of Things.
- Enable remote control - While monitoring is one-way, remote control creates a bilateral flow of information and recommended actions between the manufacturer and the device. This enables equipment manufacturers to act quickly if their product develops an issue in the field, by deploying software to clear any bugs. This will require a sea change in the way that products are designed, shifting the emphasis from user feedback to tangible device performance statistics.
- Optimise for new business opportunities - Ultimately, every manufacturer is seeking more business, and connected equipment can help unlock previously undiscovered opportunities for them. By paying more attention to product design, the data their devices generate may allow them to build new offerings such as remote service software, sell data to selected third parties, or combine data with other systems to create a more comprehensive, valuable package for other players in the industry to analyse and apply. Design optimisation to this extent enables manufacturers to alter medical equipment through remote action, and to provide the user with an experience that continues to improve as they use it more. As a result of providing improved customer service, manufacturers can begin to identify new business opportunities based on individual needs.
Ultimately, the connected medical equipment of tomorrow will have embedded intelligence at its heart, enabling clinicians and healthcare staff to benefit from improved devices in the field and better care for patients as a result. It's critical therefore, that equipment manufacturers look closely at their design processes to remain competitive in the market and create the digital-first devices that are needed for 21st century healthcare.