University campuses are normally constituted of large buildings responsible for high energy demand, and are also important as demonstration sites for new technologies and systems. This paper presents the results of achieving energy sustainability in a testbed composed of a set of four buildings that constitute the Telecommunications Engineering School of the Universidad Politécnica de Madrid. In the paper, after characterizing the consumption of university buildings for a complete year, different options to achieve more sustainable use of energy are presented, considering the integration of renewable generation sources, namely photovoltaic generation, and monitoring and controlling electricity demand. To ensure the implementation of the desired monitoring and control, an internet of things (IoT) platform based on wireless sensor network (WSN) infrastructure was designed and installed. Such a platform supports a smart system to control the heating, ventilation, and air conditioning (HVAC) and lighting systems in buildings. Furthermore, the paper presents the developed IoT-based platform, as well as the implemented services. As a result, the paper illustrates how providing old existing buildings with the appropriate technology can contribute to the objective of transforming such buildings into nearly zero-energy buildings (nZEB) at a low cost.
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http://dx.doi.org/10.3390/s21020357 | DOI Listing |
Sci Rep
January 2025
School of Information Engineering, Sanming University, Sanming, 365004, China.
Today, with the increasing use of the Internet of Things (IoT) in the world, various workflows that need to be stored and processed on the computing platforms. But this issue, causes an increase in costs for computing resources providers, and as a result, system Energy Consumption (EC) is also reduced. Therefore, this paper examines the workflow scheduling problem of IoT devices in the fog-cloud environment, where reducing the EC of the computing system and reducing the MakeSpan Time (MST) of workflows as main objectives, under the constraints of priority, deadline and reliability.
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January 2025
Institute of Theoretical & Applied Informatics, Polish Academy of Sciences (IITiS-PAN), 44-100 Gliwice, Poland.
Edge computing systems must offer low latency at low cost and low power consumption for sensors and other applications, including the IoT, smart vehicles, smart homes, and 6G. Thus, substantial research has been conducted to identify optimum task allocation schemes in this context using non-linear optimization, machine learning, and market-based algorithms. Prior work has mainly focused on two methodologies: (i) formulating non-linear optimizations that lead to NP-hard problems, which are processed via heuristics, and (ii) using AI-based formulations, such as reinforcement learning, that are then tested with simulations.
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January 2025
Institut de Recherche en Informatique de Toulouse, IRIT UMR5505 CNRS, 31400 Toulouse, France.
This review explores the applications of Convolutional Neural Networks (CNNs) in smart agriculture, highlighting recent advancements across various applications including weed detection, disease detection, crop classification, water management, and yield prediction. Based on a comprehensive analysis of more than 115 recent studies, coupled with a bibliometric study of the broader literature, this paper contextualizes the use of CNNs within Agriculture 5.0, where technological integration optimizes agricultural efficiency.
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January 2025
School of Cyber Science and Engineering, Liaoning University, Shenyang 110036, China.
Recently, there has been a growing interest in underground construction safety, during activities such as subway construction, underground mining, and tunnel excavation. While Internet of Things (IoT) sensors help to monitor these conditions, large-scale deployment is limited by high power needs and complex tunnel layouts, making real-time response a critical challenge. A delay-sensitive multi-sensor multi-base-station routing scheduling method is proposed for the IoT in underground mining.
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January 2025
Software Engineering College, Zhengzhou University of Light Industry, Zhengzhou 450002, China.
With the rapid development of IoT technology, sensors are widely used for monitoring environmental parameters. The data collected by sensors needs to be stored, and distributed storage systems provide an excellent platform to handle this vast amount of data. To enhance data reliability and reduce storage costs, erasure coding technology can be employed within distributed storage systems.
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