Digital Forensics and Internet of Things. Группа авторов

AI racism. Front. Comput. Neurosci., 10 March 2021, https://doi.org/10.3389/fncom. 2021.620281.

      5. Kamencay, P., Benco, M., Mizdos, T., Radil, R., A new method for face recognition using convolutional neural network face recognition system - state of the art. Adv. Electr. Electron. Eng., 15, 4, 663–672, 2017.

      6. Gutta, S. and Wechsler, H., Face recognition using hybrid classifiers // Pattern Recognition. IJCNN’99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), vol. 30, IEEE, Washington, DC, USA, pp. 539 – 553, 1997.

      7. Chollet., F., Keras: The Python Deep Learning library. Keras.Io, 2015, Astrophysics Source Code Library, record ascl:1806.022, Pub Date: June 2018.

      8. Januzaj, Y., Luma, A., Januzaj, Y., Ramaj., V., Real time access control based on face recognition, in: International Conference on Network security & Computer Science (ICNSCS-15), pp. 7–12, 2015.

      9. Barnouti, N.H., Al-Dabbagh, S.S.M., Matti, W.E., Face recognition: A literature review. Int. J. Appl. Inf. Syst., 11, 4, 21–31, Sep. 2016.

      10. Xiaogang, W. and Xiaoou, T., A unified frame work for subspace face recognition. IEEE Trans. Pattern Anal. Mach. Intell., 26, 9, 1222–1228, 2004.

      11. Patil, Prof. B.S. and Yardi, Prof. A.R., Real Time Face Recognition System using Eigen Faces. Int. J. Electron. Commun. Eng. Technol. (IJECET), 4, 2, 72–79, 2013.

      12. Jing, X.-Y., Wong, H.-S., Zhang, D., Face recognition based on discriminant fractional Fourier feature extraction. Pattern Recogn. Lett., 27, 1465–1471, 2006.

      13. Starovoitov, V., Samal, D., Votsis, G., Kollias, S., Face recognition by geometric features. Proceedings of 5-th Pattern Recognition and Information Analysis Conference, Minsk, May 1999.

      14. Rein-Lien, H., Face Detection and Modeling for Recognition, PhD thesis, Department of Computer Science & Engineering, Michigan State University, USA, 2002.

15.Sajjad, M. et al., Raspberry pi assisted face recognition framework for enhanced law-enforcement services in smart cities. Future Gener. Comp. Sy., 108, 4, 995–1007, November 2017. Project: Facial Expression Analysis for Law-enforcement Services.

      16. Rizon, M. et al., Face recognition using eigenfaces and neural networks. Am. J. Appl. Sci., 2, 6, 1872–1875, 2006.

      17. Agarwal, M., Jain, N., Kumar, M.M., Agrawal, H., Face Recognition Using Eigen Faces and Artificial Neural Network. Int. J. Comput. Theory Eng., 2, 4, 624–629, 2010.

      18. Shanthamallu, U.S., Spanias, A., Tepedelenlioglu, C., Stanley., M., A brief survey of machine learning methods and their sensor and IoT applications. 2017 8th Int. Conf. Information, Intell. Syst. Appl. IISA 2017, vol. 2018-January, pp. 1–8, 2018.

      19. Oh, S.H., Kim, G.W., Lim., K.S., Compact deep learned feature-based face recognition, for Visual Internet of Things J. Supercomput., 74, 6729–6741 (2018), Published: 28 November 2017.

      20. Mulla., M.R., Facial image-based security system using PCA. Int. J. Power Electron. Drive Syst. (IJPEDS), 11, 1, 417–424, March 2020.

      ^* Corresponding author: [email protected]

      2

      Smart Healthcare Monitoring System: An IoT-Based Approach

       Paranjeet Kaur

       Department of Pharmaceutical Chemistry, School of Pharmaceutical Sciences, Lovely Professional University, Jalandhar, Delhi G.T. Road, Phagwara, Punjab, India

       Abstract

      Healthcare services are looping over its economic affairs. Overgrowing elderly age of people as well as non-resistible rapid increase of complex diseases seeks the demands for the emergence of internets or digital services to revolutionize all commercial healthcare treatments. Day by day, the world is approaching out of reach healthcare services, where large proportion of people are getting unproductive due to old age and getting exposed to deadly diseases and ultimately can lead to end of the world. Fortunately, artificial intelligence has led the command over these commercialized services to make healthcare reliable in terms of cost and accessibility. “A new model known as the Internet of Things (IoT) provides a diverse applicability, including healthcare.” IoT is a network which consists as inter-related and inter-connected devices or things that are able to communication and computation over the internet. Over these years, a number of advanced application based on IoT have been proposed for convenience of patients, doctors, and caregivers. The revolution of IoT is revamping modern healthcare with social and economic prospects and also with promising technologies.

      Keywords: Internet, healthcare, sensor, hospital, patient

2.1 Introduction

The internetwork of corporeal articles or items, implanted by programming and sensors to obtain and send information among them and focal servers with no or least human remedies, is referred to as Internet of Things (IoT). IoT helps in remotely controlling and getting to these things along with a current framework. “This makes an open door for joining of physical world and PC-based framework, which brings about improved effectiveness, precision, and monetary advantage [1–5].”

      In 1999, Kevin Ashton introduced IoT; Kevin Ashton interfaces such various sensors to the corporeal item and transfers this data over the web. This IoT mechanical ability is nowadays served under express domains of presence along with computerized oilfield, living arrangement, and erection mechanization, grid, advanced clinical cure, insightful haulage, etc. [6, 7].

      Thing could be anything which has physical presence, going from an extremely little item like nanochip to enormous estimated assembling. These things are implanted with sensors, actuators, and complex programming which empower them to send and get information. In the following 5 years, IoT will be field of innovation where most speculation will be done as a result of its progressive development rate. There are distinctive versatile applications and wearable gadgets which drove patients to catch their well-being information. Emergency clinics additionally use IoT to give ongoing human services offices and to monitor their patients and work force. A portion of the IoT medicinal services applications used to screen diverse well-being angles including pulse observing, blood glucose checking, heart working, and observing physical wellness [8–12].

      Among the list of use empowered by IoT, brilliant and associated social insurance is of specific significant one. Arranged sensors, either to be put on the body or to be utilized in the live condition facilitate the possibility of gathering of our physical and psychological wellness [13]. The internet and the web have developed over the years to reach their current date structure. The development can be broadly arrayed into five stages.

      Stage 1: Advanced Research Project Agency Network. This task was fundamentally utilized for examination of research purposes by academicians as well as exploration foundations.

      Stage 2: HTML was developed during this interval and groups started to rush for name of their spaces.

      Stage 3: This stage includes value-based trade framework.

      Stage 4: The social sites: These sites have now gotten a mechanism of social communication such as Facebook, Twitter, and Groupon.

      Stage 5: “The Internet of Things (IoT)”.

It is a massive significant advancement that can effectively alter the manner in which individuals work, learn, and live [14], for example, "advanced mobile phones, internet TVs, sensors, and actuators to the internet” [15]. Web of Things works sustainably and mainly focuses on early therapeutic investigation of diseases,