The global AI enabled smart trackers market ecosystem was valued at US$ 3.2 Bn in 2018 and is expected to reach US$ XX Bn by 2026, growing at a CAGR of 20% during the forecast period. The internet of things is expected to drive the demand for smart tracking wearables in near future. IoT involves machine-to-machine connectivity and communication by cloud platforms, through which data generated by devices gets stored, analyzed, and captured. Wearable devices mainly include fitness wearable, real-time health monitoring wearable sensors, elderly tracker, fetal monitoring wearables, and others.

AI-enabled fitness trackers are expected to grow at the fastest pace during the forecast period. The AI-enabled wearable helps users track their fitness activities as well as provide guidance for food intake. Healthcare is the sector where AI-enabled wearable devices are in large demand. These wearables collect health-related data in order to monitor and provide health related awareness to the users as well as the physicians. Moreover, wearable devices for blind people for detecting obstacles on their path have also been gaining traction in recent days. The wearable developed for blind people uses ultrasounds that notify the wearer about the obstacles in order to enable to safely navigate around objects. Rising demand for AI-enabled smart Bluetooth headphones has also been one of the important factors in driving the growth of the market in recent years.

Figure 1: Ecosystem Snapshot: AI enabled smart trackers market ecosystem

The introduction of smart AI-enabled rings has also been one of the factors in accentuating the growth of AI enabled smart trackers market ecosystem in recent days. The artificial intelligence user interface embedded in this smart ring enables users to perform a variety of actions, such as controlling IoT devices, handling voice assistance such as Amazon Alexa, and others.

Table 1: AI enabled smart trackers market ecosystem: Segmentation

Smart Trackers Type	Components	Deployment	Technology
Smart Ring	CPU	Cloud	Machine Learning
Smart Bluetooth Headphones	GPU	On-Premise	NLP
Smart Fit Bands	FPGA		Computer Vision
Others	ASIC		Others
	Memory
	Others

Global AI enabled smart trackers market ecosystem  

Based on regions, North America dominated the market in 2018 and is expected to show similar trends in the coming years. Higher capita income of consumers is one the reasons behind the market growth of AI-enabled smart trackers in the region. The presence of major players such as Apple, Xiaomi, Google, and others, is also one of the important factors in driving market growth. Asia Pacific is expected to grow at the fastest pace with a CAGR of XX% during the forecast period. Increasing health-related concerns among the people in the region are driving the AI in smart tracker market in the region. At the same time, high adoption rate of smart wearables among customers in the age group of 16 to 34 years is expected to drive the AI enabled smart trackers market in the APAC region in the coming years.

The major players in AI-enabled smart trackers are Facebook, Apple, Garmin, Bragi, Xiaomi, Microsoft, HTC, Jabra, Fossil, Huawei, Fitbit, Google, Samsung, and others. The players in the market are mainly focused on mergers and acquisitions, product expansion, partnerships, and other such strategies for increasing their market share. For instance, Huami, a data driven company, announced its agreement with Timex Group, a manufacturing company, in order to develop smartwatch. Owing to this agreement, Huami will combine its app design expertise and AI technology with Timex Group’s manufacturing capabilities in order to build new generation smartwatches.

Figure 2: AI enabled smart trackers market ecosystem: Market Statistics Glimpse

There are many trends that are having an impact on the market forecast. These, when evaluated from a company’s perspective, can drive growth. Our numerous consulting projects have generated sizeable synergies across all regions and all sizes of companies.

The major players operating in the Global AI enabled smart trackers market ecosystem are as follows:

Table 2: AI enabled smart trackers market ecosystem: Key Players

Company	Ecosystem Positioning	Total Revenue	Industry	Region
Microsoft	Software provider	$110.4 Billion	Artificial intelligence	Global
Google LLC	Software provider	$136.22 Billion	Artificial intelligence	Global
IBM	Software provider	$ 79.591 Billion	Artificial intelligence	Global
Amazon	Software provider	$ 232.887 Billion	Artificial intelligence	Global
Apple	Software provider	$ 258.49 Billion	Artificial intelligence	Global

 

Very few markets have the interconnectivity with other markets like AI. Our Interconnectivity module focuses on the key nodes of heterogenous markets in detail. Internet of things, cloud computing, AR VR, and 5G integration markets are some of our key researched markets

Figure 3 –AI enabled smart trackers market ecosystem Major Interconnectivities

The integration of internet of things with artificial intelligence is also expected to create new opportunities for AI-enabled smart trackers in the near future. The internet of things will result in more wireless-enabled services and products that will create new revenue opportunities for telecom companies across the globe.

A Glance on Global AI enabled smart trackers market ecosystem Trends:

Table 3: Global AI enabled smart trackers market ecosystem: Key Trends

Trends	Technology	Impact value
Artificial intelligence powered baby monitoring devices are used to track the oxygen level, temperature, and the heart rate of babies. Machine learning and computer vision technologies are used to monitor the infant's breathing patterns in order to provide alerts to the parents if the baby is not in normal condition.	Computer Vision, Machine learning	0.34%
The machine learning-based trackers and smartwatches are used to predict the menstrual cycle of women. They record moods, pms symptoms, and help take the complete control over the health of women. The platform provides alerts of unknown health complications and the length of periodic cycle by analyzing the fertility data.	Machine learning	0.34%

 

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