ABSTRACT: IoT is the ever growing concept of connecting physical objects through internet connectivity. Internet of Things has the capability to connect everything, everyone and everywhere. It is important to accept the reality that the resources are limited and an optimum utilization of these resource have to be done for sustainability. The wastage is usually highest in the fields of water and electricity consumption. The biggest challenge for businesses is that the processes today are competitive and have to meet the customer demands without slowing down. IoT solutions such as smart irrigation system, automatic street light system and voice controlled home automation are one of the key solutions to the raising challenges. In this study prototypes of the above mentioned solutions have been built and tested to understand the potential of IoT.

India predicts about 5 billion IoT connections by 2022, and an economy of $1 trillion by 2025.And the reality is that, it’s already 2019 and IoT’s growth is slower than predicted because of some of the barriers to implementation. Some of the barrier to the growth of IoT is unawareness of consumers and cost concerns. So it is necessary for businesses to adapt business models which are efficient and suitable for IoT businesses to reach the target segment with a proper channel and a competitive value proposition. In this study a business model framework has been suggested for the prototypes built. As cost is another barrier to the IoT adoption, so the cost effectiveness of IoT solutions such as smart lighting system and smart irrigation system has been compared w.r.t to the traditional solutions.

Keywords: Business model, IoT Solutions, IoT prototyping.

ABSTRACT: The recent advancement in technology over the last decade has feature a major focus of research and development on biometric methods for the identification of individual. A biometric system offers automatic identification of an individual based on a unique feature or characteristic possessed by the individual, this feature can be physiological or biological. Features extraction is the process of extracting information from the iris image and thus a crucial stage in the iris recognitions process. In this study, we utilized an enhanced feature extraction technique based on continuous wavelet Transformation (CWT) for the extraction of iris features and reduced the runtime needed for iris templates classification. Experimental evaluation demonstrates the efficient performance of the proposed technique. Compared with Gabor filter, Fourier transform and other wavelet transforms, the proposed approach considerably reduces the computation time and improves the accuracy. The performance of continuous wavelet transform (CWT) for the feature extraction shows to be more stable and consistent even with a very high level of noisy data as compared to discrete wavelet transform (DWT). The proposed method has 0.8% FAR, 1.4% FRR and 97.8% performance recognition accuracy.

Keywords: Biometrics, Feature Extraction, Continuous Wavelet transform.

ABSTRACT: The copper deposition on the platinum and palladium nanoelectrode has been studied using cyclic voltammetry. The use of nanoelectrode platinum and palladium are defined in the study of heavy metals. The noble nanoelectrode of metal has a typical silicone processing structure. In comparison to the nanoelectrodes, the geometry of the electrode series is complex and balanced. Nanoelectrodes of platinum are found effective in detecting heavy metal. There was regular analysis of the use of the sensors. The identification constraints down to the ng /L level was accomplished by refined electrode geometry and the stripping procedures. The process was used for the study of water sample determination. Another heavy metal ion attack voltammetric reaction was studied. The SEM picture clearly observed and characterized the nanoparticle electrode by X-ray diffraction and cyclic voltammetry.

Keywords: Platinum Electrode, Nanoparticle, Heavy metal, Square Wave Voltammetry

ABSTRACT: This research paper aims to review the applications of artificial intelligence in energy and to develop a future vision for new applications. The research methodology focuses on clarifying the basic concepts of approaches to artificial intelligence (AI) and renewable energy and developing a visualisation of the link between them.

Keywords: Artificial Intelligent (AI), Solar Energy (RE).