Chang, A.: The role of artificial intelligence in digital health. In: Wulfovich, S., Meyers, A. (eds.) Digital Health Entrepreneurship. HI, pp. 71–81. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-12719-0_7
Yang, L., Henthorne, T.L., George, B.: Artificial intelligence and robotics technology in the hospitality industry: current applications and future trends. In: George, B., Paul, J. (eds.) Digital Transformation in Business and Society, pp. 211–228. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-08277-2_13
Khayyam, H., Javadi, B., Jalili, M., Jazar, R.N.: Artificial intelligence and internet of things for autonomous vehicles. In: Jazar, R.N., Dai, L. (eds.) Nonlinear Approaches in Engineering Applications, pp. 39–68. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-18963-1_2
[+]
Chang, A.: The role of artificial intelligence in digital health. In: Wulfovich, S., Meyers, A. (eds.) Digital Health Entrepreneurship. HI, pp. 71–81. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-12719-0_7
Yang, L., Henthorne, T.L., George, B.: Artificial intelligence and robotics technology in the hospitality industry: current applications and future trends. In: George, B., Paul, J. (eds.) Digital Transformation in Business and Society, pp. 211–228. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-08277-2_13
Khayyam, H., Javadi, B., Jalili, M., Jazar, R.N.: Artificial intelligence and internet of things for autonomous vehicles. In: Jazar, R.N., Dai, L. (eds.) Nonlinear Approaches in Engineering Applications, pp. 39–68. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-18963-1_2
Li, H., Ota, K., Dong, M.: Learning iot in edge: deep learning for the internet of things with edge computing. IEEE Netw. 32(1), 96–101 (2018)
Alonso, R.S., Sittón-Candanedo, I., Rodríguez-González, S., García, Ó., Prieto, J.: A survey on software-defined networks and edge computing over IoT. In: De La Prieta, F., et al. (eds.) PAAMS 2019. CCIS, vol. 1047, pp. 289–301. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-24299-2_25
Wang, T., Mei, Y., Jia, W., Zheng, X., Wang, G., Xie, M.: Edge-based differential privacy computing for sensor-cloud systems. J. Parallel Distrib. Comput. 136, 75–85 (2020)
Zhou, Z., Chen, X., Li, E., Zeng, L., Luo, K., Zhang, J.: Edge intelligence: paving the last mile of artificial intelligence with edge computing. arXiv preprint arXiv:1905.10083 (2019)
Sittón-Candanedo, I., Alonso, R.S., Corchado, J.M., Rodríguez-González, S., Casado-Vara, R.: A review of edge computing reference architectures and a new global edge proposal. Future Gener. Comput. Syst. 99, 278–294 (2019)
Ke, R., Zhuang, Y., Pu, Z., Wang, Y.: A smart, efficient, and reliable parking surveillance system with edge artificial intelligence on IoT devices. arXiv preprint arXiv:2001.00269 (2020)
Mazzia, V., Khaliq, A., Salvetti, F., Chiaberge, M.: Real-time apple detection system using embedded systems with hardware accelerators: an edge AI application. IEEE Access 8, 9102–9114 (2020)
Howard, A.G., et al.: Mobilenets: efficient convolutional neural networks for mobile vision applications. CoRR, abs/1704.04861 (2017)
Abadi, M., et al.: TensorFlow: Large-scale machine learning on heterogeneous systems (2015). Software available from tensorflow.org
[-]