Google is working with machine learning engineers from DeepMind, the world-leading artificial intelligence company, to reduce the power consumption for cooling down its considerable number of data centres. The system analyzes the relationship between various actions and their corresponding energy consumption, to select the best strategy which still maintains the safety standards.
FarmLogs is a free platform using AI to help farmers increase profitability and reduce waste. FarmLogs contains four products: FarmLog Lite(free), FarmLogs Essentials, FarmLogs Complete, Add-Ons.
ConserWater is a platform using satellite data and AI to help farmers reduce water wastage and predict exactly how much water farmers need to give to their crops at any time. It also includes AI-based irrigation recommendations, plant disease detection, irrigation leak detection, farm-specific weather, and so on.
In order to estimate the compressive and flexural strengths of environmentally friendly jarosite mixed concrete, an effective prediction model based on the modified Elman neural network (also known as feed-through Elman neural network (FTENN), a recurrent neural network) tuned with back-propagation (BP) algorithm is developed. Jarosite is a toxic waste produced by the zinc industry that needs to b
In this study, an improved bald eagle search optimization algorithm (IBES) is utilized to develop home energy management systems for smart homes. This research is crucial for energy field researchers who are interested in optimizing energy consumption. The primary objective is to optimally manage load demand, reduce the average peak ratio, lower electricity bills, and enhance user comfort. To acco
Internal burnishing operation is a prominent solution to improve the hole quality. In this study, minimum quantity lubrication (MQL) system parameters, including the diameter of the nozzle ( N ), impingement angle ( I ), the pressure of the compressed air ( P ), the flow rate of the lubricant ( L ), and the distance between the nozzle and workpiece ( D ) are optimized for decreasing the total ener
Supply chain network design (SCND) problems are essential in formulating strategic decisions on the number of facilities, network facility location, and plant capacity, to ensure the optimal delivery of products from manufacturers to end consumers. On the other hand, assembly line balancing (ALB) problems provide details on operational decisions which encompass production levels and inventories an
A picture fuzzy set (PFS) is the extended version of an intuitionistic fuzzy set (IFS) and can deal with dubious and imprecision information. Dombi aggregation models are powerful mathematical tools utilized to aggregate human opinions and information in different fields, including social networking, data analysis, architecture, and neurosciences. Bonferroni means (BM) and geometric Bonferroni mea
The incorporation of Internet of Things (IoT) expertise into eco-friendly environments and eco-tourism has profoundly enriched our way of life. The collaboration among the Green Internet of Things (GIoT), big data, and machine learning offers innovative solutions for ecological challenges and sustainable practices. Despite its potential, IoT presents challenges such as heightened energy consumptio
This research work supports the perception of the multi-criteria group decision-making (MCGDM) approach to foster the problem of suitable vehicle selection on the cylindrical neutrosophic number (CNN) environment. The purpose of this research is to choose a suitable vehicle under specific criteria that are related to economic, environmental, and social factors throughout all age classes to enhance
Cotton is a crucial crop that has a significant impact on the global economy, and the timing of the harvest is crucial for maximizing the yield and quality of cotton fiber. However, predicting and detecting the harvesting stage of cotton plants is a complex task that requires analyzing various factors such as plant growth, leaf senescence, and boll maturity. Traditional methods for harvesting pred
To realize and handle power consumption details of sustainability, power consumption efficiency measurement for an electromechanical system within a long-term period is critical. Practically, data envelopment analysis (DEA) is useful to measure power consumption efficiency of an electromechanical system for yielding relative efficiencies of peer decision-making units (DMUs). Generally, traditional