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With the Arrival of robotics and Artificial intelligence in the last few years we have been experiencing a significant change in the robotic applications used for regular activities. Nowadays, cost effective cleaning robots produced by industry are far away from the purchasing capability of normal householders. In this paper, we have proposed an AI model to develop a minimum expense floor cleaning Robot, we developed a functional floor cleaning robot model as well as the methods of the indoor navigation and location system. This robot can find the region and cleaning a certain region of a floor independently, no human intervention for cleaning and waste disposal. [ABSTRACT FROM AUTHOR]

Internet of things-Any device that is connected to internet represents internet of things. A thing can be a sensor or device or anything that physically exist in the real world. Now-a-days-IOT plays a very major role in every aspect of life. IOT sensors made efficiency and convenience for human life. Internet of things in the field of irrigation is very beneficial to farmers. In IoT-based smart irrigation, system monitors the crop condition with the help of sensors and automating the irrigation system. IoT-based smart farming is highly efficient than traditional model. IOT in agriculture has given a very big impact. [ABSTRACT FROM AUTHOR]

Information refers to meaningful data. When sensitive information is transmitted from sender to receiver, there might be chances for data to get captured. The captured data might be modified or some content might be removed by the intruder or the data might be lost. The Cryptographic principles like confidentiality, integration, authentication, access control were very important to safeguard the information. Although there were many cryptographic techniques like AES. There might be chances for the attacker or the hacker to peep or look at the encrypted data. Now-a-days providing security in social networking sites is very difficult. [ABSTRACT FROM AUTHOR]

Agriculture plays a significant role in improving economy of the nations. India is an agrarian nation and its economy principally dependent on crop profitability. The effect of environmental change in India, the vast majority of the farming crops are being seriously influenced regarding their performance over a time of the most recent twenty years. Anticipating the crop yield ahead of it's cultivate would assist the farmers for taking suitable measures for taking suitable precautions for storage and selling. Precise yield anticipation requires major conception of the association amid yield and these intuitive elements, and to unearth such association needs both extensive datasets and incredible strategies. In this article, we developed a Deep-Neural-Networks (DNNs) method that takes benefit of conventional models. This technique was establish to have a leading forecast exactness; with a Root-Mean-Square-Error (RMSE) being 15%of the mean yield and 50% of the standard-deviation for the test dataset utilizing estimated environment information. Our empirical outcomes suggested that this approach essentially outperformed other techniques like Lasso, Shallow Neural Networks (SNN), and RegressionTree(RT). The results additionally discovered those biological elements had a big impact on the crop production than genotype. [ABSTRACT FROM AUTHOR]