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Green information and communication systems for a sustainable future
\"This book includes the fundamental concepts, applications, algorithms, protocols, new trends, challenges, and research results in the area of Green Information and Communication Systems. It is a resource that offers knowledge on core and specialized issues, making it highly suitable for both the new and the experienced researcher in the field. The book covers network design theoretical and practical perspectives. It includes how Green ICT initiatives and applications can play a major role in reducing CO2 emissions, and focuses on industry and how it can promote awareness and implementation of Green ICT. The book discusses scholarship and research in green and sustainable IT for business and organizations and uses the power of IT to usher sustainable in other parts of an organization. The book is for business and management educators, management researchers, doctoral scholars, university teaching personnel, policy makers as well as higher academic research organizations. It is also a good resource for Industrial and Management training organizations all over the world\"-- Provided by publisher.
Book
Green Communications and Networking
This book presents recent advances in green communications and networking for wired, wireless, and smart-grid networks. These technologies not only provide the emission reduction and energy savings in Information and Communication Technology (ICT) products and services, but also enable low GHG emissions in other industries, such as electric power. The text covers new algorithms, protocols, and network architectures to make cellular networks more energy efficient. It also includes a rich set of references in each chapter.
eBook
The Atlas of AI
The hidden costs of artificial intelligence, from natural
resources and labor to privacy and freedom What happens
when artificial intelligence saturates political life and depletes
the planet? How is AI shaping our understanding of ourselves and
our societies? In this book Kate Crawford reveals how this
planetary network is fueling a shift toward undemocratic governance
and increased inequality. Drawing on more than a decade of
research, award-winning science, and technology, Crawford reveals
how AI is a technology of extraction: from the energy and minerals
needed to build and sustain its infrastructure, to the exploited
workers behind \"automated\" services, to the data AI collects from
us. Rather than taking a narrow focus on code and algorithms,
Crawford offers us a political and a material perspective on what
it takes to make artificial intelligence and where it goes wrong.
While technical systems present a veneer of objectivity, they are
always systems of power. This is an urgent account of what is at
stake as technology companies use artificial intelligence to
reshape the world.
eBook
YOLOv8n-BWG-enhanced drone smoke detection: Advancing environmental monitoring efficiency
The precise monitoring and localization of industrial exhaust smoke emissions play a crucial role in environmental management. Existing methods encounter challenges like intricate detection environments, small-scale targets, and extensive model parameters. This study presents an advanced drone smoke detection model, YOLOv8n-BWG, building on YOLOv8. It introduces a novel BC2f structure into the backbone network, leveraging an adaptive query mechanism to minimize computational and storage demands while boosting feature extraction efficiency. Additionally, the study employs a dynamic sample allocation strategy to refine the loss function, enhancing the model’s sensitivity to small targets. It also integrates a lightweight convolution, GSConv, in place of traditional convolution techniques. GSConv employs a channel grouping approach, streamlining model parameters without sacrificing accuracy. Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. Significantly, deploying YOLOv8n-BWG on drones yielded promising outcomes in smoke detection, offering innovative approaches and insights for effective smoke monitoring practices.
Journal Article
A Review of Energy Efficiency and Power Control Schemes in Ultra-Dense Cell-Free Massive MIMO Systems for Sustainable 6G Wireless Communication
The traditional multiple input multiple output (MIMO) systems cannot provide very high Spectral Efficiency (SE), Energy Efficiency (EE), and link reliability, which are critical to guaranteeing the desired Quality of Experience (QoE) in 5G and beyond 5G wireless networks. To bridge this gap, ultra-dense cell-free massive MIMO (UD CF-mMIMO) systems are exploited to boost cell-edge performance and provide ultra-low latency in emerging wireless communication systems. This paper attempts to provide critical insights on high EE operation and power control schemes for maximizing the performance of UD CF-mMIMO systems. First, the recent advances in UD CF-mMIMO systems and the associated models are elaborated. The power consumption model, power consumption parts, and energy maximization techniques are discussed extensively. Further, the various power control optimization techniques are discussed comprehensively. Key findings from this study indicate an unprecedented growth in high-rate demands, leading to a significant increase in energy consumption. Additionally, substantial gains in EE require efficient utilization of optimal energy maximization techniques, green design, and dense deployment of massive antenna arrays. Overall, this review provides an elaborate discussion of the research gaps and proposes several research directions, critical challenges, and useful recommendations for future works in wireless communication systems.
Journal Article
Radiofrequency-electromagnetic field exposures in kindergarten children
The aim of this study was to assess environmental and personal radiofrequency-electromagnetic field (RF-EMF) exposures in kindergarten children. Ten children and 20 kindergartens in Melbourne, Australia participated in personal and environmental exposure measurements, respectively. Order statistics of RF-EMF exposures were computed for 16 frequency bands between 88 MHz and 5.8 GHz. Of the 16 bands, the three highest sources of environmental RF-EMF exposures were: Global System for Mobile Communications (GSM) 900 MHz downlink (82 mV/m); Universal Mobile Telecommunications System (UMTS) 2100MHz downlink (51 mV/m); and GSM 900 MHz uplink (45 mV/m). Similarly, the three highest personal exposure sources were: GSM 900 MHz downlink (50 mV/m); UMTS 2100 MHz downlink, GSM 900 MHz uplink and GSM 1800 MHz downlink (20 mV/m); and Frequency Modulation radio, Wi-Fi 2.4 GHz and Digital Video Broadcasting-Terrestrial (10 mV/m). The median environmental exposures were: 179 mV/m (total all bands), 123 mV/m (total mobile phone base station downlinks), 46 mV/m (total mobile phone base station uplinks), and 16 mV/m (Wi-Fi 2.4 GHz). Similarly, the median personal exposures were: 81 mV/m (total all bands), 62 mV/m (total mobile phone base station downlinks), 21 mV/m (total mobile phone base station uplinks), and 9 mV/m (Wi-Fi 2.4 GHz). The measurements showed that environmental RF-EMF exposure levels exceeded the personal RF-EMF exposure levels at kindergartens.
Journal Article
Can Fintech Promote Sustainable Finance? Policy Lessons from the Case of Turkey
This study contributes to sustainable finance literature by exemplifying promotion of sustainable finance through fintech solutions for emerging market economies by presenting the case of Turkey. Turkey is one of the largest emerging market economies in the world with a strong banking system and high adoption of technology, so it has great potential to benefit from fintech solutions to boost sustainable finance. For the case analysis, the data used came from a research platform for a Turkish start-up ecosystem, Turkish regulations, and documents released on Turkey’s sustainable finance strategies by Turkish and international institutions. We found that Turkey has made remarkable progress in increasing financial inclusivity for underbanked individuals and SMEs via providing contactless payment and contract systems and microfinance by mobile carriers and other online platforms. Turkey was also able to promote the responsible consumption goal for sustainable development by improving fintech solutions on payment systems with educational content on this goal. With upcoming developments such as the sandbox environment in Istanbul Financial Center, fintech solutions using Big Data, AI, and blockchain could emerge much faster with collaboration between banking and fintech sectors and regulatory institutions to better assess climate-related financial risks and form a national carbon trading mechanism.
Journal Article
IT-Enabled Sustainable Innovation and the Global Digital Divides
This article investigates the impact of information and communication technologies (ICTs), human capital, institutional settings, socio-economic, and environmental parameters on sustainable innovation (SI) using archival data for 127 economies from 2008 to 2017. We developed an econometrics research framework for investigating factors influencing SI on a global scale. We found that ICT variables, such as ICT access and ICT broadband network, positively influence sustainable innovation in conjunction with the socio-economic and political parameters. Despite differences among economies in terms of ICTs, socio-economic development, and educational attainment, ICTs are the significant drivers of sustainable innovation and economic growth. We observed a growing digital divide among nations within the context of the knowledge-based economy and the expansion of digital commerce, particularly in the least developed countries and Africa, a phenomenon impeding sustainable innovation growth. To the best of our knowledge, this is the first study that empirically investigates the global digital divide from sustainable innovation perspectives. The results of this study suggest that to tackle the digital divide issues, policymakers and educational institutes need to perform constructive educational reform in higher education curricula, particularly concerning STEM programs, which should reflect the necessary skills and competencies for deploying emergent technologies. In addition, ICT should be considered part of a country’s critical infrastructure, particularly investment in the broadband networks regarded as the backbone of today’s innovation.
Journal Article
GAM-enhanced deepLabv3+ for accurate burn scar extraction in karst regions from remote sensing images
Forest fires pose a severe threat to ecosystems, and accurate burn scar extraction is critical for post-disaster recovery and ecological management. This study proposes an attention mechanism enhanced deep learning model for semantic segmentation of burn scars in Karst regions, aiming to address challenges such as fragmented terrain and complex vegetation patterns. The model integrates ResNet50 as the backbone network to leverage its robust feature extraction capability and residual connections, mitigating gradient vanishing problem. To enhance multi-scale feature learning while avoiding grid artifacts, we optimize the Atrous Spatial Pyramid Pooling (ASPP) module by reducing dilation rates to (1, 3, 5). Furthermore, a novel Global Attention Module (GAM) is introduced after the decoder branches to dynamically recalibrate channel-spatial dependencies, enabling precise segmentation in heterogeneous backgrounds. Experiments demonstrate the model’s superiority with a mean Intersection over Union (mIoU) of 91.82% and mean accuracy (mAcc) of 95.73%, outperforming mainstream models (e.g., DeepLabV3 + , SegFormer, Mask2former) and traditional methods. The model demonstrates outstanding extraction accuracy and strong generalization capabilities; however, there remains room for optimization in terms of parameter quantity and inference speed. Future work will further explore lightweight design and real-time performance enhancement strategies. This study combines deep learning with GIS and remote sensing technology to construct a single region dataset for typical fire events in Huaxi District, Guiyang City, Guizhou Province in 2024. An efficient framework for extracting burn spots from karst landforms is proposed, which can provide real-time reference for the impact assessment, ecological restoration, and carbon flux estimation of this fire event in the region.
Journal Article
Handbook of green information and communication systems
This book gives a comprehensive guide on the fundamental concepts, applications, algorithms, protocols, new trends and challenges, and research results in the area of Green Information and Communications Systems.
eBook