Massive multiple-input multiple-output or massive MIMO system has great potential for 5th generation (5G) wireless communication systems as it is capable of providing game-changing enhancements in area throughput and energy efficiency (EE). This work proposes a realistic and practically implementable EE model for massive MIMO systems while a general and canonical system model is used for single-cell scenario. Linear processing schemes are used for detection and precoding, i.e., minimum mean squared error (MMSE), zero-forcing (ZF), and maximum ratio transmission (MRT/MRC). Moreover, a power dissipation model is proposed that considers overall power consumption in uplink and downlink communications. The proposed model includes the total power consumed by power amplifier and circuit components at the base station (BS) and single antenna user equipment (UE). An optimal number of BS antennas to serve total UEs and the overall transmitted power are also computed. The simulation results confirm considerable improvements in the gain of area throughput and EE, and it also shows that the optimum area throughput and EE can be realized wherein a larger number of antenna arrays at BS are installed for serving a greater number of UEs.
Growth of population and the inception of new devices every day comes with an incessant rise in energy consumption and has brought great challenges in terms of energy management at the consumer side. With the evolution of technology, smart meters (SMs) are not only considered merely as tools to measure energy consumption but act as a main resource of energy management systems. The application of SM spans over a wide range of advantages, including accurate billing data, information of utilization at the user end, the establishment of two-way communication and remote control of the user equipment. SM is the most essential element of a smart power grid that with the help of any smart energy management system (SEMS), assesses, measures, controls, implements and communicates power allocation, utilization, and consumption at both, single device, and network level. Data provided by the SMs is used by power supply companies to revolutionize power distribution and consumption through various techniques such as, non-intrusive load monitoring and demand-side management (DSM). For efficient data gathering and utilization, internet of things (IoT) is emerging as a key partner in the power industry leading to effective resource management. This paper provides presentation, deployment, and validation of an IoT based SEMS strategy and its related benefits to overcome challenges of energy management at consumer side. The presented SEMS incorporates various communication interfaces and protocols to integrate with any software-based smart solution. In this work, Entrack software is used for data gathering and analysis. As a proof of concept, the presented system is tested and implemented in 4 different buildings of a well-known private company in Pakistan, i.e., Stylo Pvt. Ltd. The case study analysis in this work shows the effectiveness of the presented IoT based SEMS.INDEX TERMS Energy management system (EMS), Internet of Things (IoT), smart meter (SM), smart grid (SG).
The increasing price of and demand for energy have prompted several organizations to develop intelligent strategies for energy tracking, control, and conservation. Demand side management is a critical strategy for averting substantial supply disruptions and improving energy efficiency. A vital part of demand side management is a smart energy management system that can aid in cutting expenditures while still satisfying energy needs; produce customers’ energy consumption patterns; and react to energy-saving algorithms and directives. The Internet of Things is an emerging technology that can be employed to effectively manage energy usage in industrial, commercial, and residential sectors in the smart environment. This paper presents a smart energy management system for smart environments that integrates the Energy Controller and IoT middleware module for efficient demand side management. Each device is connected to an energy controller, which is the inculcation of numerous sensors and actuators with an IoT object, collects the data of energy consumption from each smart device through various time-slots that are designed to optimize the energy consumption of air conditioning systems based on ambient temperature conditions and operational dynamics of buildings and then communicate it to a centralized middleware module (cloud server) for management, processing, and further analysis. Since air conditioning systems contribute more than 50% of the electricity consumption in Pakistan, for validation of the proposed system, the air conditioning units have been taken as a proof of concept. The presented approach offers several advantages over traditional controllers by leveraging real-time monitoring, advanced algorithms, and user-friendly interfaces. The evaluation process involves comparing electricity consumption before and after the installation of the SEMS. The proposed system is tested and implemented in four buildings. The results demonstrate significant energy savings ranging from 15% to 49% and highlight the significant benefits of the system. The smart energy management system offers real-time monitoring, better control over the air conditioning systems, cost savings, environmental benefits, and longer equipment life. The ultimate goal is to provide a practical solution for reducing energy consumption in buildings, which can contribute to sustainable and efficient use of energy resources and goes beyond simpler controllers to address the specific needs of energy management in buildings.
Bariatric surgery is a prevalent procedure due to the high incidence of obesity and comorbidities. Upper gastrointestinal endoscopy is one of the procedures used to evaluate the patient before surgery. However, its role is questionable. The incidental findings during endoscopy are variable including inflammatory diseases, and ulcers, and epithelial and stromal tumors. Herein a report of two obese sisters with incidental gastric carcinoids was diagnosed in prebariatric surgery endoscopy. Case Summary. 35- and 41-year-old female patients presented with obesity and BMI of 102 and 46 kg/m2, respectively. Both patients underwent upper gastrointestinal endoscopy as part of presurgical evaluation. Multiple polyps were indentified in both patients, and biopsy was taken. Histological examination revealed tumors that were formed by nests of epithelial cells. The cells have eosinophilic cytoplasm and monomorphic nuclei, typical morphology of neuroendocrine tumors. Conclusions. (1) Upper gastrointestinal endoscopy is an important procedure for prebariatric surgery evaluation. (2) Gastric carcinoid is a rare tumor with higher incidence among obese patients.
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