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The rising price and demand for energy are significant issues for the food sector, which consumes a substantial amount of energy throughout the supply chain. Hence, improving energy efficiency has become an essential priority for the food sector. However, most food businesses have limited awareness of the recent technological advancements in real‐time energy monitoring. Thus, the concept of "Internet of Things" (IoT) has been investigated to increase the visibility, transparency, and awareness of various energy usage levels. This paper presents a case study of a beverage factory where the implementation of an IoT‐enabled sensing technology based on the embodied product energy (EPE) model helped to reduce the energy consumption. This arrangement made provision for the collection of real‐time energy data within a food production system to support informed and energy‐aware operational decisions, which lead to optimized energy consumption and significant savings of approximately 163,000 kWh in the year 2017. Practical applications: Given the importance of energy efficiency and Internet of Things (IoT), especially in the food manufacturing industry, this research reports a baseline application at a beverage company in India. The results allowed the company to use energy more efficiently to have an advantage over its competitors and better market positioning. More data could be incorporated into the energy management system with the use of IoT. The availability and accuracy of such valuable data would help managers to make better energy‐efficient decisions. [ABSTRACT FROM AUTHOR]

SUMMARY Energy demand is increasing rapidly because of developments in the agricultural, industrial, commercial and transportation sectors. Improved lifestyle and population rise are other reasons for the increase in energy demand. The development of an electricity allocation model will help in the proper allocation of the energy sources to meet the future electricity demand in India. In this paper, an attempt has been made to develop a fuzzy-based linear programming, optimal electricity allocation model (OEAM) that minimizes the cost and determines the optimum allocation of different energy sources to the centralized and decentralized power generation in India. The potential of energy sources, energy demand, efficiency of the energy systems, emission released by the energy systems and carbon tax for the emissions released by each system are the main factors that influence the pattern of electricity distribution and are used as constraints in the model. Executing this model results in an optimal electricity distribution pattern. The results indicate that the commercial energy sources such as coal, nuclear and hydro would meet nearly 68% of total electricity demand and that the remaining 32% of the electricity demand will be met by the renewable energy sources, namely, wind, biomass, biogas, solid waste, cogeneration and mini hydel for the year 2020. Various scenarios are also developed by varying the demand, potential, emission and carbon tax. This study will help in the formation of strategies for effective utilization of energy sources in India. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]