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Forecasting is a common statistical venture in commercial enterprise, in which it facilitates to inform decisions about the scheduling of manufacturing, transportation and provides a guide to long-term strategic planning. The automobile sales forecast plays a vital role in business strategy for generating profit for an automobile enterprise corporation. However, it is a very challenging process due to the high level of complexity and uncertainty involved within the competitive world. This study proposed a hybrid model the usage of an Adaptive Multiplicative Triple Exponential Smoothing Holt-Winters (AHW) method and Backpropagation Neural Networks (BPNNs) to forecast automobile sales. The Indian automobile sales statistics has been used for both training and testing purposes. The result of the proposed method outperforms than the single forecasting model in terms of automobile sales forecasting.

Nowadays, the usage of Wireless Sensor Networks (WSN) with Internet of Things (IoT) is increasing in many commercial and industrial applications to perform various tasks inexpensively. Internet of Things (IoT) is the expansion of smart objects and Wireless Sensor Networks by interfacing distributed and identifiable communication devices. The accessibility of imbalanced resources and heterogeneous IoT communication leads to vitality utilization imperatives. This study proposed an improved Chaotic Whale Optimization model to improve the utilization of vitality. The proposed system result shows better vitality effectiveness in coordinates WSN-IoT environment.