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Uttarakhand is endowed with perennial rivers and large network of both rain fed and ice fed rivers that provide immense scope for development of Hydro Power in the State. Hydro power is the clean energy which generates electricity at zero fuel cost. Regulatory issues, Transmission /Power evacuation issues, Environmental concerns, Inter-state perspectives, Law and order issues, Dearth of good contractors, Natural effects, Political issues, Land acquisition problem, Resettlement and Rehabilitation issues, Locational disadvantages, Budgetary requirements, Private sector involvement and Longer gestation period are some of the obstructions which are hindering the development of hydro power plants. This paper reviews the available literature to identify several barriers affecting the development of Hydro Power in Uttarakhand.

Abstract The globe is presently perusing technologies that entirely automate the processes with negligible losses. To achieve this, the world has initiated their automation from private bodies like home, school, etc. Thus, our paper is created to aid their process. This paper describes the solid-state switching using wireless networks. The proposed paper deals with the replacement of solid-state device instead of application of relays in home automation, as the performance of relays are not very effective in switching at higher inrush currents and they require an adequate environment for its better performance. Solid state devices have advantages like less power consumption, better life span, easy control, etc. Thus, the use of solid-state devices improves the performance of the entire home automation system. This proposed paper uses a protocol DALI (Digitally Addressable Lighting Interface) which controls switching of light resistive loads and improves communication. The soft switching operation of the circuit operates with the wireless network and improves the ability of carrying loads and has a strong controlling ability. The design and circuit framework can be adapted to any of the switch-controlled circuits which is relayed on solid state device.

In Saudi Arabia, housing projects account for almost half of the total electricity consumed by the construction industry because of the large number of housing projects compared to other types of buildings. This paper proposes a quantitative approach using a multiple linear regression assessment model to predict the energy cost and environmental cost of housing building in Saudi Arabia. It was developed to assist house owners in Saudi Arabia in estimating the monthly energy cost and associated operational carbon cost according to several predictor parameters. Based on related literature, these parameters were reviewed and discussed by experts from the Ministry of Housing. They included building location, wall type, number of occupants, window type, envelope insulation, building age, building area, number of air-conditioning units and their systems, and lighting system. The model development process included five main stages: collecting the energy and carbon cost data from completed operating housing units, categorizing the collected data based on parameters, diagnosing the quality of gathered data and filtering outlier data if any, building and generating a model, and lastly, testing and validating the model. More than 77 datasets were collected across the country during different times of the year. The findings of this study reveal that the relationship between the number of users and the building area with the energy cost is significant and that the number of users is more correlated to the energy cost than the age of the building or the number of central air conditioners installed. Moreover, the results show that the developed model has the ability to predict energy and carbon costs with high accuracy. The developed model serves as a decision support tool for householders and decision makers in the Ministry of Housing to control the predicted parameters. This would be beneficial for the housing unit owners for allocating constrained budgets.

With the advent of enhancing environmental and fossil energy concerns, sustainability that can be done with the effective utilization of presently used energy sources, is of major concern. The world of today is working hard to solve energy related problems, such as, energy supply security, emission control, economy and conservation of energy etc. A great potential lies in the hand of automotive engineers and scientists to use these exhisting reserves of petrolium products effectively. In this present study, effect of compression ratio on the performance and emissions of the diesel engine at various loads is done. While conducting the experiment compresssion ratio range is kept from 18 to 22. It is observed that compression ratio 21 is giving maximum Brake thermal efficiency at part as well as full load. Brake specific fuel consumption and Brake specific energy consumption is found minimum at compression ratio 21. Article DOI: http://dx.doi.org/10.20319/mijst.2016.22.3247 This work is licensed under the Creative Commons Attribution-Non-commercial 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.

Significant changes in society were emphasized as being required to achieve Sustainable Development Goals, a need which was further intensified with the emergence of the pandemic. The prospective society should be directed towards sustainable development, a process in which technology plays a crucial role. The proposed study discusses the technological potential for attaining the Sustainable Development Goals via disruptive technologies. This study further analyzes the outcome of disruptive technologies from the aspects of product development, health care transformation, a pandemic case study, nature-inclusive business models, smart cities and villages. These outcomes are mapped as a direct influence on Sustainable Development Goals 3, 8, 9 and 11. Various disruptive technologies and the ways in which the Sustainable Development Goals are influenced are elaborated. The investigation into the potential of disruptive technologies highlighted that Industry 5.0 and Society 5.0 are the most supportive development to underpin the efforts to achieve the Sustainable Development Goals. The study proposes the scenario where both Industry 5.0 and Society 5.0 are integrated to form smart cities and villages where the prospects of achieving Sustainable Development Goals are more favorable due to the integrated framework and Sustainable Development Goals’ interactions. Furthermore, the study proposes an integrated framework for including new age technologies to establish the concepts of Industry 5.0 and Society 5.0 integrated into smart cities and villages. The corresponding influence on the Sustainable Development Goals are also mapped. A SWOT analysis is performed to assess the proposed integrated approach to achieve Sustainable Development Goals. Ultimately, this study can assist the industrialist, policy makers and researchers in envisioning Sustainable Development Goals from technological perspectives.

Multistep power consumption forecasting is smart grid electricity management’s most decisive problem. Moreover, it is vital to develop operational strategies for electricity management systems in smart cities for commercial and residential users. However, an efficient electricity load forecasting model is required for accurate electric power management in an intelligent grid, leading to customer financial benefits. In this article, we develop an innovative framework for short-term electricity load forecasting, which includes two significant phases: data cleaning and a Residual Convolutional Neural Network (R-CNN) with multilayered Long Short-Term Memory (ML-LSTM) architecture. Data preprocessing strategies are applied in the first phase over raw data. A deep R-CNN architecture is developed in the second phase to extract essential features from the refined electricity consumption data. The output of R-CNN layers is fed into the ML-LSTM network to learn the sequence information, and finally, fully connected layers are used for the forecasting. The proposed model is evaluated over residential IHEPC and commercial PJM datasets and extensively decreases the error rates compared to baseline models.

Disposal facilities are essential components of waste management. Even with the increased emphasis on waste minimisation, reuse and recycling, the amounts of waste residues requiring disposal are continuously increasing. Urban centres are faced with a multitude of problems owing to increasing quantities of waste residues coupled with decreasing availability of land in urban areas. Optimal use of land for the disposal facilities is a necessity for the civic authorities. Landfills are still the most used method of disposal, especially in developing countries. Costs and environmental risks associated with disposal facilities vary with respect to time in a complex manner. The success of a long-term plan for solid waste disposal critically depends on the best use of landfills with respect to time. In this paper, an integer linear programming based optimisation model is presented. This model addresses multiple objectives including costs and environmental risk for multi-period planning. A case study of solid waste disposal in the capital city Delhi, India, is presented, demonstrating the utility of the proposed model.

In view of the climate change threat, India has recently committed to reduce greenhouse gas emissions to 35% by 2030 relative to 2005 levels. Energy efficiency in buildings offers the greatest potential for saving energy at the lowest cost. This paper reviews current energy consumption trends in the residential building sector of India and traces various initiatives by the government to reduce dependence on fossil fuels in terms of regulatory framework, green building rating systems, fiscal incentives and institutional mechanisms affecting energy demand management. Further, the paper provides an overview of various barriers and challenges in implementing energy efficiency programmes in housing along with suggestions to strengthen the institutional framework and create awareness to accelerate energy efficiency programmes for reducing CO2 emissions.