The Internet of Things has become extremely important in both consumer and industrial markets. The availability of high bandwidth connections with the growth of 5G networks is giving rise to new IoT solutions in Smart Cities, Automotive, Industry 4.0, Supply Chain, Healthcare, and Energy.
It seems we are bound to be more and more surrounded by connected devices in the following years. “Things” come in all shapes and sizes. In the consumer market there are smart home devices, smart appliances, smart speakers, and so on. The projections estimate the total IoT market value will be in the trillions.
AI has emerged as a fantastic enabler of connected Things: anything from Natural Language Processing in smart speakers, to predictive maintenance of devices, to many advanced deep learning applications.
There has been some coverage of “Intelligence of Things”. Connected devices generating data from various sensors provide opportunities to analyse, mine, and discover AI models. These can then be deployed for application in areas such as predictive maintenance.
When it comes to autonomic IoT, the emerging trend is Edge Computing. It is a decentralized computing infrastructure in which computing resources and application services can be distributed along the communication path from the data source to the cloud. Edge computing is faster and more optimized as it allows devices to take immediate action. There are many advantages to executing AI models at the edge.
In many applications where instantaneous decisions need to be made the delays of round-tripping from a Cloud-based data centre for AI model execution could be prohibitive. Internet connectivity might have unacceptable latencies or even be off-line. The connected devices as well as the gateways are becoming increasingly powerful in storage, computation, and networking optimizations. Pushing computations and intelligence to the edges reduces the latency of the decision executions. This could be critical in many industrial and consumer IoT applications.
Another, more current example in this Covid-19 era is Intelligent IoT Edge Computing for Medical Things. Due to the lock-down, connected monitoring, connected tests, and telecare are providing tremendous opportunities for remote patient monitoring in these difficult times. The pandemic has stressed the care providers and hospitals — especially when the number of patients increases sometimes exponentially.
Remote monitoring of connected devices and the intelligence pushed to the edges of the monitoring devices becomes critical in alleviating some of the pressure from the caregivers and even saving lives. For instance, recently GE Healthcare introduced Mural Virtual Care Solution, which aggregates data and monitoring from several systems and allows virtual monitoring through “near real-time data from ventilators, patient monitoring systems, electronic medical records, labs, and other systems.” The solution “allows one clinician to monitor several patients at once, supplementing existing monitoring devices in patients’ rooms.” At its core, it is an intelligent virtual ICU system with tremendous benefits both for the caregivers and patients — monitoring the progress of the patients across geographical distances.
In conclusion, the connectivity of devices in our homes, hospitals, cities, and industries is becoming ubiquitous. A number of technologies such as 5G, Cloud, and AI are critical for robust and pragmatic solutions with IoT. Connectivity is exploding but more importantly, edge computing is becoming critical. It realizes the benefits of IoT in real-time. The faster intelligence is applied where the devices and people are, the better. The edge intelligence and its application is a critical trend that will accelerate in the coming years.