Article Details

The Internet of Behavior extends from the Internet of Things (IoT), the interconnection of devices that results in a vast variety of new data sources. This data might be specific to a customer-data provided through a company’s app. But, more often, companies are gathering non-customer information by “sharing” across connected devices.

A single device, like a smart phone, can track online movements as well as real-life geographic position. It’s not difficult for companies to link smart phone with our laptop, in-home voice assistant, house or car cameras, and maybe cell phone records (texts and phone calls). Companies are increasingly using such information to inform how they sell, but it’s not all targeted advertising. Data reaped from the IoT can be used for other reasons which are as follows:

• Reduction in Human Error.
• Organizations can test the effectiveness of their campaigns, both commercial and non-profit.
• Health providers can measure the activation and engagement efforts of patients.
• Policymakers could even personalize content, affecting laws and current programs.

What does the IoB mean and contribute?

The purpose of the IoB is to capture, analyze, understand and respond to all types of human behaviors in a way that allows tracking and interpreting those behaviors of people using emerging technological innovations and developments in machine learning algorithms. People’s behaviors are monitored and incentives or disincentives are applied to influence them to perform towards a desired set of operational parameters. What is really relevant about IoB is that it is not only descriptive (analyzing behavior), but proactive (detecting which psychological variables to influence to bring about a certain outcome).

The IoB influences consumer choice, but it also redesigns the value chain. While some users are wary of providing their data, many others are happy to do so as long as it adds value - datadriven value. For companies, this means being able to change their image, market products more effectively to their customers or improve the Customer Experience (CX) of a product or service. Hypothetically, information can be collected on all facets of a user’s life, with the ultimate goal of improving efficiency and quality. IoB turn all the data collected from user’s online activities into something useful usually means profit for companies. IoB is a combination of three fields:

• Technology
• Data Analytics
• Behavioral Science

IoT Vs IoB

The IoT is a network of interconnected physical objects that gather data and exchange information and data over the internet whereas the IoB does is make sense of this data and attach it to specific human behaviors such as purchasing or following a specific brand online.

Benefits & pitfalls of the IoB

• We don’t have to be concerned about our data.
• The IoT surely converts data to information. But it’s too early to know whether the IoB can translate knowledge of us into real wisdom.

Benefits & pitfalls of the IoB

Tiny AI can make it possible for the tech community to deploy any complex algorithm from an edge device. For instance, any user could conduct medical image analysis using their smartphones. They may even be able to partake in autonomous driving without the help of a cloud. With so many of these possibilities being limited to your average edge devices, users will also be able to improve on data security and privacy Now this doesn’t necessarily mean that cloud centers will become outdated. Instead, they will beused for very high-performing computing algorithms such as for DNA analysis. To do so, cloudsystems will have to deal with huge amounts of data in a matter of hours. Again, Tiny AI will beable to help here by making hyper-efficient AI systems.
Research into Tiny AI is critical in enabling AI to realize its full potential. The challenge for both researchers and technology firms is managing the trade-off between reducing the size of a model, through distillation techniques for instance, and maintaining accuracy and high performance for inference. As Tiny AI is closer to the human experience, the accuracy needs to be high. There’s no room for error with things like autonomous vehicles. It’s also vital to make Tiny AI algorithms at the edge secure, transparent and ethical, as they’ll be deployed in real-life environments. Tiny AI could fundamentally alter the way we interact with many devices and will be necessary to create the next wave of context-aware consumer devices. It looks set to improve a myriad services and technologies including, but not limited to, voice assistants, autocorrect, and image processing in cameras, autonomous driving, precision farming, connected healthcare, Industry 4.0 and intelligent logistics. It will also make many new applications possible.