The Opportunity That Lies in IoT Data for Analytics Entrepreneurs

My fascination with the proliferation of the Internet of Things (IoT) began during the COVID-19 pandemic. Like many people, I spent a significant amount of time indoors and decided to take up running to stay fit. Initially, I thought running was just about getting a good pair of shoes and comfortable workout clothes. However, I soon discovered a vast ecosystem built around this simple activity.

My phone automatically tracked my steps, providing daily updates on my activity levels, distance covered and step count. This piqued my interest, leading me to invest in a smartwatch. Through this device, I was introduced to online platforms that helped manage running sessions. What surprised me the most was the sheer number of people using these platforms – millions of smartwatch users syncing their data to online databases in real time. This realization sparked a deep curiosity in me: If a single IoT device, such as a smartwatch, could create an entire ecosystem, what other possibilities exist within the expanding realm of IoT?

The origins of IoT trace back to 1989, when David Nichols and his colleagues at the Massachusetts Institute of Technology (MIT) created the first IoT device [1]; a key milestone was reached in 2008 when the number of connected devices surpassed the global population [2]. The following year saw the advent of Bluetooth 3.0 [3], which enabled faster data transfer speeds of up to 20 megabits per second (Mbps), accelerating IoT adoption.

Several advancements over the years contributed to the IoT boom, including the development of low-power wide-area network (LPWAN) technology [4], reduced production costs of industrial IoT sensors [5] and the rise of IoT platforms. Between 2015 and 2017, major technology companies entered the IoT space – Amazon launched Amazon Web Services (AWS) IoT Core, Microsoft introduced Azure IoT Hub and Google unveiled Google IoT Core. These platforms paved the way for widespread IoT adoption. By 2021, the number of connected devices exceeded nonconnected devices, and by 2022, IoT ranked among the top three most impactful technologies according to the World Economic Forum [6]. Estimates suggest that by 2025, the economic impact of IoT could range from $2.7 trillion to $6.2 trillion per year.

The expansion of IoT devices has led to an explosion in data generation. IoT devices are equipped with sensors that continuously collect information from everyday objects, from household appliances to industrial machinery. According to a 2020 forecast by the International Data Corporation (IDC), the number of IoT devices is expected to reach 41.6 billion by 2025, generating an astonishing 79.4 zettabytes (ZB) of data [7].

Data is the foundation of the IoT ecosystem. The real-time insights provided by IoT devices enable businesses to make data-driven decisions, optimize operations and improve efficiency. Even at a basic level, leveraging descriptive and diagnostic analytics allows companies to significantly enhance their products and services.

The integration of artificial intelligence (AI) with IoT further amplifies data analytics capabilities. AI algorithms have become more sophisticated, enabling organizations to analyze vast and complex datasets with greater precision. This fusion of AI and IoT allows businesses to uncover subtle patterns and trends that would have otherwise gone unnoticed.

Returning to my personal journey with running, I became intrigued by the businesses that emerged from the IoT data ecosystem. A notable example is Strava, a fitness-tracking platform founded in 2009. Strava records users’ activity data, offering insights such as route summaries, elevation changes, speed, timing, power and heart rate. Beyond just tracking workouts, Strava integrates social networking features, allowing users to share their progress with others. This illustrates how IoT data can be harnessed to create innovative and profitable enterprises.

As an analytics professional, I see the future of IoT not only as a vast data landscape but also as a realm of entrepreneurial opportunity. With the anticipated growth of IoT devices and the increasing volume of data they generate, analytics professionals are positioned to become not just data consumers but also innovators, developing solutions embedded within the IoT ecosystem.

Despite the immense potential of IoT, challenges remain, particularly regarding data security and ethics. Most IoT-generated data is user-driven [8], often containing personal, health or sensitive information. This raises significant privacy concerns. A notable example is the March 2024 New York Times report, which revealed that companies such as GM, OnStar, LexisNexis and Verisk Analytics had collected and sold driver behavior data to insurance companies without user consent [9].

While such challenges exist, they do not overshadow the opportunities within IoT and data analytics. According to IoT Analytics, between 2016 and 2024, the top 20 IoT startups collectively received nearly $6.7 billion in funding [10], with investment expected to grow. This demonstrates increasing support for IoT-driven innovations.

The rapid evolution of IoT presents both challenges and opportunities. As devices become more interconnected and data generation increases, the need for ethical data handling, security measures and regulatory frameworks will be crucial and is an opportunity in itself. At the same time, the entrepreneurial potential within IoT is vast. By responsibly harnessing IoT data, analytics professionals can drive innovation and create impactful solutions in this ever-expanding digital ecosystem.

References

1. Salunke, V.M. and S. Mahajan, 2024, “The evolution and implications of the Internet of Things,” March, DOI: 13140/RG.2.2.16409.39527.
2. Evans, D., 2011, “The Internet of Things: How the next evolution of the internet is changing everything,” White Paper, Cisco.
3. https://majorhifi.com/the-difference-between-bluetooth-3-0-4-0-4-1-4-2-explained/
4. https://www.techtarget.com/iotagenda/definition/LPWAN-low-power-wide-area-network
5. https://www.statista.com/statistics/682846/vr-tethered-hmd-average-selling-price/
6. Manyika, J., M. Chui, J. Bughin, R. Dobbs, P. Bisson and A. Marrs, 2013, “Disruptive technologies: Advances that will transform life, business, and the global economy,” McKinsey Global Institute, May.
7. https://ieeexplore.ieee.org/document/9210375/references#references
8. Pomella, K., 2024, “The impact of IoT on customer data collection and analysis,” September 16, https://kenpomella.com/blog/the-impact-of-iot-on-customer-data-collection-and-analysis.
9. https://www.nytimes.com/2024/03/11/technology/carmakers-driver-tracking-insurance.html
10. Kaman, Z., 2024, “IoT startup landscape 2024: 7 notable insights,” IOT Analytics, July 31, https://iot-analytics.com/iot-startup-landscape.