Data Science Challenges in Terms of the Internet of Things

It´s common knowledge that the amount of data generated by one person, company, or social groupings has increased exponentially in the last decade. As of recently, only 90% of the world’s data has been developed [1].

Thanks to the Internet of Things (IoT), generating and accessing information has become increasingly easier. Clients’ data, competitive companies, or different markets are at hand nowadays. Nevertheless, the tremendous amount of data generated has made it harder to consume and, at the same time, reduced its time of reliability [2].

The overall benefit of the information’s volume is lost when the time that takes to analyze it is exponential to the amount of data. What use will the benefits have if a company needs to develop a report in less than 20 minutes, but it takes 3 hours just to load the data? What would happen in the extreme case of autonomous and cooperative vehicles where the analysis and response time must be immediate?

Such problems commonly occur for two main reasons: the difficulty to organize the non-standardized information or the cost generated by uploading polished and structured data to the cloud for upcoming analysis.

A strategy destined to solve this problem has been incorporating a more significant number of servers, destined exclusively for these processes’ data consumption and latency reduction by avoiding data uploads to the cloud [3].

Nevertheless, the standardized data challenge remains unsolved. It is imperative to rapidly integrate this information in an organized manner in order to guarantee the products and services’ quality and competitiveness in the future.

[1] Bradshaw, L. (2012). B u s i n e s s h o r i z o n s q u a r t e r l y // f a l l 2 0 1 2. U.S. Chamber of Commerce Foundation, 5–8.

[2] Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2016). Edge Computing: Vision and Challenges. IEEE Internet of Things Journal, 3(5), 637–646. https://doi.org/10.1109/JIOT.2016.2579198

[3] Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2016). Edge Computing: Vision and Challenges. IEEE Internet of Things Journal, 3(5), 637–646. https://doi.org/10.1109/JIOT.2016.2579198