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Present days the world is surviving with respect to the software products. The development of the software product is a challenging issue and to run with the competitive world rapid development of software products are necessary. It is not enough to go with the traditional software development products like waterfall model, spiral model and all. Here we proposed the SCRUM TOOL, one of the effective techniques of Agile Methodology. Agile is an incremental and timeframe iterative approach. It supplies the software developers with a working framework for traditional software development practices like waterfall model. Although the traditional models are best suited for small products where there is no changing requirements but not suitable for the products which have rapidly changing requirements and thus here we recommend SCRUM methodology. In this approach we can develop the software product by taking the regular feedback from the customer through review meetings. So whenever the customer requests the changes we can upgrade the product with respect to those changes and can also develop the product more efficiently and rapidly.

In this paper we have proposed face recognition door lock system using raspberry pi for security purpose. Implementation of the system is for monitoring whether any unknown person is entering in to the door. We have established communication with electronic devices through face detection with the help of Pi camera Raspberry Pi platform. For software coding Python and Open CV libraries are used. In order to get accurate and clear picture of an intruder we have proposed Haar classifier method for face detection. As soon as the person enters near the door, pi camera captures the image and face detection process is done then if it matches with database images then the door is unlocked otherwise a message with the picture of a person will be sent to the registered mobile through GSM and LAN network.

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Farming is very labour intensive and needs timely action. In smart farming many activities of farming are conducted by machines which run on electricity. Electricity is one of the key elements of smart farming. The quality and cost of the agriculture produce are mostly determined by quality of the available energy and energy utilized. Though India is agriculture rich country, many rural areas are still not provided with sufficient electricity for the farming. In the current scenario of depleting natural energy resources like fossil fuels, using electricity generated from fossil fuels is expensive. Hence, there is a strong need to shift to nonconventional renewable and natural energy resources. Solar energy is one such energy available in abundance in India, however, the existing solar energy harvesting technologies which uses solar cell technology is able to convert very little portion of the available solar energy. The conversion efficiency of solar cells is found to be 16-18%. The authors in this paper present a more efficient solar energy harvesting technology which uses nanomaterial for improving conversion efficiency and machine learning technology to maximize the collection of solar radiation by continuously tracking the path of the SUN in all the seasons.