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Introduction: Internet of things (IoT) compose of million of devices connected together over the internet. IoT plays a vital role now a days and especially in future, the most of the monitoring and data collection. The data should be secure while collection and as well in the process of transferring till the destination whether Service Organization Control (SOC) or to cloud for storage. In this paper, a secure IoT based intelligent monitoring system is proposed. Methods: An intelligent IoT station that interacts via cellular connection to relay data to the cloud is constructed using the Waspmote platform. The algorithm is injected to automatically filter and only keep the new data for transfer to avoid redundancy. The advanced encryption standard (AES) 256-bit method is enabled for onboard data encryption and then the generated cipher text is transmitted. The encrypted data is then stored over the cloud to ensure privacy. Moreover, the mobile application (mApp) is developed to be installed on handheld devices for calling the secure data from the cloud, decrypting it, and displaying it as per user input, whether real-time or historical. Results and Discussion: The encryption algortihm helps in securing the proposed monitoring system from brute force, man in the middle, phishing, spoofing, and denial of service (DoS) attacks. The results of the real testbed experimentation demonstrate the complexity evaluation and reliability of IoT monitoring systems with end-to-end data security in terms of encryption algorithm delay and data rate, respectively. [ABSTRACT FROM AUTHOR]

The present research assesses the amount of the water in the biological tissues is using He-Ne laser and a Si-based one-dimensional (1-D) photonic waveguide through an experimental in situ monitoring method. The principle of measurement of water relies on the variation of density of water with respect to the transmitted energy (output energy), where the transmitted efficiency of the signal is determined through both experiment and theory. The measured spectrum was compared with the spectrum simulated by using the plane wave expansion method and was in good agreement with the simulated one. Further the accuracy of the investigation as well as the relation between output energy and density is found. The error of computation is found to be less than 10-5 which suggests that the proposed method is suitable for the investigation of biological tissues. [ABSTRACT FROM AUTHOR]

Machine learning using the ANN approach is presented in this paper to design 101 channels of optical DEMUX in the range of 1300–1400 nm. This work is used to envisage the optical parameters of silicon grating structure such as the thickness of SiO and Si which are the decisive factors to allow the desired signal through the structure to realize optical DEMUX. This is accomplished by training an ANN model with a few pre-defined optical DEMUX parameters which are obtained beforehand by the plane wave expansion method. Here, the ANN model is implemented in the Tensor Flow framework of Google Colaboratory Network (Colab) which consists of five hidden layers of ReLU activation besides the input and output linear activation nodes. Besides this, the optical parameters collected from the ANN model are used to simulate through the PWE method for validation by observing the reflectance characteristics curve and found that most of the values are satisfied to realize the optical VLSI DEMUX. The outcomes of the present work could be beneficial in the field of optical VLSI systems pertaining to the optical interconnect. [ABSTRACT FROM AUTHOR]

The design of a Covid-19 testing kit is proposed in this research using a photonic crystal structure (PhC) and a violet laser beam. The basic principle of this structure relies on the phenomenon of absorbance reflectance and transmission at the signal of a 412 nm laser beam. Finally, the transmitted light energy through the PhC structure is the conclusive factor to detect the types of virus which is the function of the reflectance and absorbance. The reflected light energy is computed by plane wave expansion (PWE) whereas the absorbance of light energy is obtained through numerical computation. The notable advantages of this technique are that the virus related to Covid-19 can be recognized by observing the colour of transmitted energy through a photo energy meter. Finally, the outcomes of the research affirm that the sample could be Covid-19 if the output energy would be infrared (IR). Similarly, the sample could be a normal coronavirus, if the output energy would lie within the visible regime. [ABSTRACT FROM AUTHOR]