2. E-Health applications¶

This section covers the identified e-Health applications.

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Interesting links:

https://github.com/tpthanhan/ResourceProvisionFogComputing/tree/master/iFogSim-master/topologies

2.1. HealtCam Application Flowchart¶

Ref: D. Cantillo, B. Cervantes and J. Cardona (2021). “HealthCam: Machine Learning Models on Mobile Devices for Unhealthy Packaged Food Detection and Classification.” IEEE HEALTHCOM, pp. 1-6.

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2.2. EGC application¶

Ref: Dadashi Gavaber, M., & Rajabzadeh, A. (2021). BADEP: Bandwidth and delay efficient application placement in fog‐based IoT systems. Transactions on Emerging Telecommunications Technologies, 32(8), e4136.

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2.3. e-Health workflow application¶

Ref: Yang, R., Wen, Z., McKee, D., Lin, T., Xu, J., & Garraghan, P. (2020). Fog orchestration and simulation for iot services.

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2.4. Insulin pump application¶

Ref: Mehran, N., Kimovski, D., & Prodan, R. (2019). MAPO: a multi-objective model for IoT application placement in a fog environment. In Proceedings of the 9th International Conference on the Internet of Things (pp. 1-8).

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2.5. Mental health care application¶

Ref: Mehran, N., Kimovski, D., & Prodan, R. (2019). MAPO: a multi-objective model for IoT application placement in a fog environment. In Proceedings of the 9th International Conference on the Internet of Things (pp. 1-8).

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2.6. Patient-Medicine Administration application¶

Ref: Khalid, A., ul Ain, Q., Qasim, A., & Aziz, Z. (2021). QoS based optimal resource allocation and workload balancing for fog enabled IoT. Open Computer Science, 11(1), 262-274.

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3. Surveillance applications