Using an IoT system in precision agriculture removes the need for direct spraying by people, which is the focus of this study. When it comes to better managing agricultural needs, the Internet of Things plays a significant role. Currently, insecticides and fertilizers are sprayed by hand, endangering the nervous system of the sprayer and resulting in countless deaths. Farming in today’s world is hampered by a lack of trained labor and rapidly shifting environmental circumstances. Traditional farming methods need to be rethought in order to keep pace with today’s agricultural needs. Agriculture automation is therefore necessary, and this can be done via Wireless Sensor Networks and Internet of Things (IoT).

Current research on fingerprint recognition is discussed in the following article. Focuses on earlier investigations of fingerprint recognition systems and a brief review of fingerprint recognition’s conceptual and structural frameworks are presented in this paper The fundamentals of fingerprint recognition have been explained. A pre-processing phase is used to eliminate irrelevant data and enhance the visibility of added character by employing an enhancement technique for biometric data acquisition. An additional stage extracts fingerprint features from the output of the pre-processing phase. The database template is compared to the newly obtained feature. This study aims to evaluate recent work on fingerprint recognition systems and elucidate fingerprint recognition steps gradually and present descriptions of fingerprint records with features.

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