Opportunities, Limitations, Risks and Challenges in IoT Systems

Opportunities, Limitations, Risks and Challenges in IoT Systems

During the first collaborative discussion of the ‘Deciphering Big Data’ module at Essex, I learned that the Internet of Things (IoT) is a network of interconnected physical devices that are embedded with sensors, software, and connectivity, enabling them to collect and exchange data. Evaluating the rationale behind IoT involves considering the opportunities, limitations, risks, and challenges associated with the process of data collection.

• Opportunities: Real time massive volume of data, providing information for analysis, allowing fast decision making and facilitating the development of automated models.

• Limitations: IoT comes in different structurers and formats; data architects need to develop robust data integration to handle the complexity of data effectively. The lack of standards between IoT devices makes difficult to integrate and analyze data from different sources, which can hinder data analysis and the development models.

• Risks: Some of the risks involve data security, resulting in ethical implications. Selvaraj and Sundaravaradhan (2016) mention that privacy is the major concern in the IoT due to its less storage space to process some encryption methods. The extensive data collection in IoT raises ethical concerns in regards of consent, transparency, and fair use of data. Data scientists must address ethical considerations, such as protecting privacy, avoiding biases in algorithms, and ensuring data is used in ways that benefit society.

• Challenges: The growing of data generated by loT devices need scalable and robust infrastructure. There is a need of designing and implementing data storage management systems that can handle the complexity of loT data and at the same time, it is crucial to ensure compliance with data protection regulations.

In conclusion, loT offers a tremendous potential for organization or individuals to gain innovation and to optimize decision-making process, but it also implies limitations, risks and challenges that require thoughtful examination and strategies to tackle effectively.

References:

Selvaraj, S. and Sundaravaradhan, S. (2019). Challenges and opportunities in IoT healthcare systems: a systematic review. SN Applied Sciences, 2(1). doi:https://doi.org/10.1007/s42452-019-1925-y.

Wickham, H. (2014). Tidy data. Journal of Statistical Software, 59, 1–2

Redman, T. (2013). Data’s Credibility Problem. [online] Harvard Business Review. Available at: https://hbr.org/2013/12/datas-credibility-problem [Accessed 11 May 2023].