Energy data classification at the edge: a comparative study for energy efficiency applications
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Software
Link
https://link.springer.com/content/pdf/10.1007/s10586-023-04142-3.pdf
Reference48 articles.
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2. Greco, L., Percannella, G., Ritrovato, P., Tortorella, F., Vento, M.: Trends in IoT based solutions for health care: moving AI to the edge. Pattern Recognit. Lett. 135, 346–353 (2020). https://doi.org/10.1016/j.patrec.2020.05.016
3. Sittón-Candanedo, I., Alonso, R.S., García, Ó., Gil, A.B., Rodríguez-González, S.: A review on edge computing in smart energy by means of a systematic mapping study. Electronics (2020). https://doi.org/10.3390/electronics9010048
4. Zhang, Y., Li, B., Tan, Y.: Making AI available for everyone at anywhere: a survey about edge intelligence. J. Phys. Conf. Ser. 1757(1), 012076 (2021). https://doi.org/10.1088/1742-6596/1757/1/012076
5. Li, W., Liewig, M.: A survey of AI accelerators for edge environment. In: Rocha, Á., Adeli, H., Reis, L.P., Costanzo, S., Orovic, I., Moreira, F. (eds.) Trends and Innovations in Information Systems and Technologies, pp. 35–44. Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-45691-7_4
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