Information security is one of the most important factors to be considered when secret information has to be communicated between two parties. Cryptography and steganography are the two techniques used for this purpose. Cryptography scrambles the information, but it reveals the existence of the information. Steganography hides the actual existence of the information so that anyone else other than the sender and the recipient cannot recognize the transmission. In steganography the secret information to be communicated is hidden in some other carrier in such a way that the secret information is invisible. In this paper an image steganography technique is proposed to hide audio signal in image in the transform domain using wavelet transform. The audio signal in any format (MP3 or WAV or any other type) is encrypted and carried by the image without revealing the existence to anybody. When the secret information is hidden in the carrier the result is the stego signal. In this work, the results show good quality stego signal and the stego signal is analyzed for different attacks. It is found that the technique is robust and it can withstand the attacks. The quality of the stego image is measured by Peak Signal to Noise Ratio (PSNR), Structural Similarity Index Metric (SSIM), Universal Image Quality Index (UIQI). The quality of extracted secret audio signal is measured by Signal to Noise Ratio (SNR), Squared Pearson Correlation Coefficient (SPCC). The results show good values for these metrics.

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Monitoring systems based on artificial intelligence (AI) and wireless sensors are in high demand and give exact data extraction and analysis. The main objective of this paper is to detect the most appropriate plant development parameters. This paper has the concept of reducing the hazards in agriculture and promoting intelligent farming. Advancement in agriculture is not new, but the AI-based wireless sensor will push intelligent agriculture to a new standard. The research goal of this work is to improve the prediction state using image processing-based machine learning techniques. The main objective of the paper, as described above, is to detect and control cotton leaf diseases. This paper comprises several aspects, including leaf disease detection, remote monitoring system depending on the server, moisture and temperature sensing, and soil sensing. Insects and pathogens are typically responsible for plant diseases that reduce productivity if not timely. This paper presents a method to monitor the soil quality and prevent cotton leaf diseases. The proposed system suggested uses a regression technique of artificial intelligence to identify and classify leaf diseases. The information would be delivered to farmers through the Android app after infection identification. The Android app also allows soil parameter values like moisture, humidity, and temperature to be displayed along with the chemical level in a container. The relay may be on/off to regulate the motor and chemical sprinkler system as required by using the Android app. In the proposed system, the SVM algorithm delivers the best accuracy in detecting various diseases and demonstrates its efficiency in the detection and control by the improvement of cultivation for the farmers.

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A rising proportion of older people has more demand on services including hospitals, retirement homes, and assisted living facilities. Regaining control of this population’s expectations will pose new difficulties for lawmakers, medical professionals, and the society at large. Smart technology can help older people to have independent and fulfilling lives while still living safely and securely in the community. In the last several decades, the number of sectors using robots has risen. Comrade robots have made their appearance in old human life, with the most recent notable appearance being in their care. The number of elderly individuals is increasing dramatically throughout the globe. The source of the story is the use of robots to help elderly people with day-to-day activities. Speech data and facial recognition model are done with AI model. Here, with the Comrade robotic model, elder people’s healthcare system is designed with better analysis state. The aim is to put in place a simple robotic buddy to determine the health of the old person via a headband that has been given to them. Comrade robot may do things like senior citizens home automation, home equipment control, safety, and wellbeing sensing, and, in emergency situation, routine duties like navigating in the outside world. The fear that robotics and artificial intelligence would eventually eliminate most of the jobs is increasing. It is anticipated that, in order to survive and stay relevant in the constantly shifting environment of work, workers of the future will need to be creative and versatile and prepared to identify new business possibilities and change industry to meet challenges of the world. According to the research, reflective practice, time management, communicating, and collaboration are important in fostering creativity.