By 2025, it is anticipated that the world will have around 75 billion IoT connected devices

Smart devices are getting smarter, learning out habits and relieving us from the routine. Intelligent devices and the infusion of futuristic technologies have made everyday life easier. Internet of Things (IoT) is leading the change with its technology spreading over various devices including home basics.

As of 2020, the world has around 27 billion IoT connected devices. The number is anticipated to grow to 75 billion by 2025, according to Statista. Door locks, thermostats, fridges, televisions, video doorbells and security cameras can be summoned remotely with the help of IoT. Intelligent devices make ageing in place for elders much more viable. Smart products are simpler for them to use and can be managed remotely by other family members. The agriculture sector is also a high beneficiary of IoT. Both crop farmers and livestock farmers use IoT sensors to monitor their yield. Even though when the opportunities of IoT are predicted to change the world upside down, it has a set of flaws that needs to be addressed.

The fear of an explosion of data that underpins these advances is causing trouble for those creating products, services and supporting infrastructure. Generally, IoT devices rely on a cloud-based platform to process data that they have collected from devices. Even though when the model has its side of benefits, intelligent edge stoops to improve the IoT devices to another level.

Internet of Things (IoT) limitations

Internet of Things (IoT) phenomenon ubiquitously connects things providing key physical data and further processing of that data in the cloud to deliver insights. Since IoT links to millions of devices, it stores all the data in the cloud. Sending data to and from the cloud has its drawbacks.

• Energy and bandwidth- Transmitting data uses energy and bandwidth. More data management leads to more cost spent on finite resources.

• Latency- Sending data to the cloud introduces latency, which limits the effectiveness of certain applications.

• Privacy and security risks- Transforming information introduces privacy and security risks. Data collected by a smart device at home or office reveals a lot of information; sometimes even personal content is also stored. The assurance that data is being safely shifted to the cloud is linear. If hackers get the handle of it, the situation could worsen.

Intelligent Edge in Internet of Things (IoT)

Intelligent edge is the process where data is analyzed and aggregated in a spot close to where it is captured in a network. The big driver behind the rise of intelligent edge is the technology's need in IoT. As the number of IoT devices collecting data and transforming it to the cloud for processing increases, the need to address certain challenges became increasingly pressing.

By using intelligent edge, a device can perform decision making analysis on a closely connected device rather than sending the data to a cloud. This reduces the aforementioned latency, energy consumption and bandwidth use while enabling users to keep private data within the confines of their own infrastructure.

Machine learning is the key technology that accelerates close decision making possible. The edge devices use a pre-trained machine learning model to make a decision based on new data being collected by local sensors.

Use cases of Intelligent Edge 

Receiving signals based on body language: Much of human communication is delivered using more than just words. Tone, facial expressions, gestures, etc. are some of the other representations we obtain to communicate or understand one another. Using intelligent edge in IoT device will enable signals that better inform the natural-feeling interaction experiences. This can be leveraged by using object and gesture recognition, voice recognition, tonal analysis and Natural Language Processing (NLP).

Alerting owners of mishaps: Intelligent devices enhance safety. It senses the problematic circumstances and alerts the owner, enabling them to react accordingly. For example, smart home kits could be trained to recognize danger signals such as alarms going off, a person's sudden fall, glass breaking or a tap left dripping or running.

The future ahead

The future of Internet of Things (IoT) is anticipated to leverage more devices with intelligent edge features. The AI accelerated future could include neuromorphic or in-memory computing, spiking neural networks or even quantum AI. This will also alleviate the ability to implement the actual training of machine learning algorithm at the edge.

In a nutshell, IoT espoused with intelligent edge will open the door for a further human-AI interface. It will be a promising time for designers, engineers, businesses and consumers with technology becoming more and more sustainable.