Collaborative Discussion 1
The Data Collection Process (units 1-3)
The discussion focused on the IoT with the remit to discuss the opportunities, limitations, risks and challenges associated with large-scale data collection thereby aligning to module learning outcomes 1 and 2.
Summary of Discussion Post
In my initial post I discussed the rapid growth of IoT and how analytics of the resulting data creates opportunities for business optimisation across multiple fields including improved and strealined marketing and customer experiences, healthcare, farming and smart homes and cities. I highlighted the importance of effective data wrangling and data privacy, and discussed how undertaking pre-processing within an edge or fog environment may address potential data privacy and latency issues.
My colleagues’ posts further highlighted the importance of optimising data processing and the potential risks of edge or fog computing. Colleagues flagged the potential for pre-processing steps to filter out ‘anomalies’ that may include meaningful data. Reflecting on this comment I additionally considered the potential for edge-based pre-processing to introduce bias, and further reading on this led to the suggetsion in my summary post that the issues of inappropriate filtering may be mitigated at least in part by utilisation of a hybrid edge and cloud approach where raw data is forwarded to the cloud as required in order to refine AI models and improve edge device performance (Balbir, 2024).
Colleagues also highlighted potential risks of fog/edge computing in relation to data privacy and cybersecurity. In relation to data privacy, processing of data at the edge may reduce the need to upload sensitive data to cloud servers (Balbir, 2024), however ensuring compliance with regards to personal data collection and processing on multiple devices remains a challenge (EmbedUR, 2025).
With regards to cybersecurity, the utilisation of multiple fog gateways and nodes will increase the potential attack surface, furthermore due to branched edge architecture, a single compromised node may propagate to others, leading to a cascading security breach (EmbedUR, 2025; Palla, 2022)
In conclusion, the rapid growth of IoT devices presents significant opportunity for business development and environmental sustainability across multiple fields. However the quality of the data is crucial for the generation of unbiased, accurate data analytics and ensuring data privacy requirements are met must remain a top priority.
References
Balbir (2024). What role does cloud computing have with edge AI. Available at: https://medium.com/infiniticube/what-role-does-cloud-computing-have-with-edge-ai-2989d2b381eb (Accessed: 10 September 2025).
EmbedUR (2025). The Advantages & Risks of Edge AI: Why Businesses Can’t Ignore It. Available at: https://www.embedur.ai/the-advantages-risks-of-edge-ai-why-businesses-cant-ignore-it/ (Accessed: 10 September 2025).
Palla, K. (2022) Fog computing: Security benefits and risks, The National CIO Review. Available at: https://nationalcioreview.com/articles-insights/technology/fog-computing-security-benefits-and-risks/ (Accessed: 10 September 2025).
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