This study explores the intersection of smart manufacturing and the Sustainable Development Goals (SDGs) from a poverty reduction perspective. Smart manufacturing refers to the integration of advanced technologies, su...
This study explores the intersection of smart manufacturing and the Sustainable Development Goals (SDGs) from a poverty reduction perspective. Smart manufacturing refers to the integration of advanced technologies, such as automation, artificial intelligence, and data analytics, into the manufacturing sector to improve productivity, efficiency, and sustainability. The SDGs, adopted by the United Nations in 2015, provide a comprehensive framework to address global challenges, including poverty eradication. This study examines how smart manufacturing can reduce poverty by aligning with the SDGs. It investigates the potential of smart manufacturing technologies to create employment opportunities, enhance income levels, and improve living conditions in low-income communities. By leveraging advanced technologies, smart manufacturing can facilitate the transformation of traditional industries, enable the growth of small and medium-sized enterprises (SMEs), and promote inclusive economic development. The study employs a multidisciplinary approach, drawing on literature from the fields of engineering, economics, and sustainable development. It explores case studies from various regions and industries to provide empirical evidence of the impact of smart manufacturing on poverty reduction. Also, it examines the challenges and barriers that need to be addressed to ensure that the benefits of smart manufacturing are equitably distributed and reach those most in need. The findings of this study contribute to both academia and policymaking. They provide insights into how smart manufacturing can be harnessed to achieve the SDGs, particularly the goal of poverty reduction. The study highlights the importance of technological innovation and its potential to create inclusive and sustainable economic growth. It also offers recommendations for policymakers, industry stakeholders, and development organizations on how to leverage smart manufacturing to address poverty and promote sustain
Graph are ubiquitous because the fields of application are varied. Well-known examples are social networks, biological networks and path-finding in road networks. Real-world graphs processing is very challenging becau...
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Breast cancer is the most common disease among women and has become one of the leading causes of death in women worldwide. Early breast cancer detection is very crucial to attain an optimum medical treatment. This pap...
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ISBN:
(数字)9798331504144
ISBN:
(纸本)9798331504151
Breast cancer is the most common disease among women and has become one of the leading causes of death in women worldwide. Early breast cancer detection is very crucial to attain an optimum medical treatment. This paper presents a hexagonal slotted Ultra-Wideband (UWB) textile antenna for breast cancer detection systems. The proposed antenna has a dimension of
$44\times 38\text{mm}_systems^systems$
, with a substrate made of felt material characterized by a relative permittivity,
$\varepsilon_{r}$
of 1.44, a loss tangent,
$tan\delta$
of 0.044, and a thickness,
$h$
of 1.5 mm. The radiating element and ground plane of the antenna are using ShieldIt Super and the thickness is set to be 0.17 mm. The proposed antenna sensor consists of a hexagonal slotted monopole antenna and a partial ground plane. The partial ground plane technique is used to enhance the performance as well as to tune in the desired frequency range. The antenna operates from 2 to 10 GHz with a maximum gain of 3.62 dBi. In addition, the proposed textile antenna has a compact structure, wide bandwidth, lightweight, and flexible, thus meeting the requirements of breast cancer detection systems.
In this paper, we present OVERTAKE, an opportunistic routing protocol for Time-Slotted Channel Hopping (TSCH). OVERTAKE combines (1) opportunistic routing, (2) concurrent transmissions and (3) TSCH. We show that this ...
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ISBN:
(数字)9781728143514
ISBN:
(纸本)9781728143514
In this paper, we present OVERTAKE, an opportunistic routing protocol for Time-Slotted Channel Hopping (TSCH). OVERTAKE combines (1) opportunistic routing, (2) concurrent transmissions and (3) TSCH. We show that this novel combination enables low-latency, central scheduling withstanding node failures. Our initial results show its ability to withstand node failures of up to 40% of nodes of a flow while keeping minimal latency.
Packet transmission is a function of signal strength and distance in a wireless sensor network (WSN). The interval between the source node and sink node is of high significance in a wireless sensor network. This work ...
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The automobile industry is one of the most thriving and rapidly growing industries in the modern world and with the recent advancement in technologies, it is inevitable to avoid the merger of different technological s...
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In recent years, the optimization of thermal power plants has become a critical area of research, driven by the urgent need to enhance energy efficiency and reduce emissions. This paper proposes a novel approach lever...
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ISBN:
(数字)9798331542108
ISBN:
(纸本)9798331542115
In recent years, the optimization of thermal power plants has become a critical area of research, driven by the urgent need to enhance energy efficiency and reduce emissions. This paper proposes a novel approach leveraging Reinforcement Learning (RL) techniques to optimize the operation of thermal power plants in real-time. RL, a branch of machine learning, offers a promising framework for decision-making in dynamic and uncertain environments, making it well-suited for the complex and nonlinear nature of power plant operations. By integrating RL algorithms with streaming data from sensors and control systems, our proposed methodology enables adaptive and autonomous control of key parameters such as air-fuel ratio and combustion temperature. This approach not only maximizes combustion efficiency but also minimizes emissions of harmful pollutants such as NOx, SOx, and particulate matter. Through simulation studies and real-world experiments, we demonstrate the effectiveness of our proposed approach, paving the way for the next generation of intelligent and sustainable power plant operation. We present a conceptual framework for RL-based control of thermal power plants highlighting potential benefits such as combustion efficiency, improved environmental performance, and enhanced operational flexibility.
Intelligence is an abstract topic and Turing test, as an external behavior detection method, provides a scientific method to test representational artificial intelligence. In this work, we briefly discuss the categori...
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This paper presents the design and development of a real-time monitoring system for DC microgrids in solar farms using an MQTT-based IIoT device integrated with Node-RED. The system incorporates voltage and current se...
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ISBN:
(数字)9798331542108
ISBN:
(纸本)9798331542115
This paper presents the design and development of a real-time monitoring system for DC microgrids in solar farms using an MQTT-based IIoT device integrated with Node-RED. The system incorporates voltage and current sensors connected to solar panels, with an ESP32 microcontroller reading data from the sensors to calculate power output. This data is transmitted to a Raspberry Pi server via a WiFi network, utilizing the MQTT protocol for efficient and reliable communication. Node-RED manages and visualizes the data flow, providing a user-friendly interface through its dashboard for monitoring real-time voltage, current, and power readings. This integration of IIoT devices with Node-RED streamlines data collection, processing, and visualization, enhancing solar farms' overall monitoring and control. The proposed system's scalability allows for the seamless addition of new sensors and microgrids without substantial modifications, addressing the need for flexible expansion in large-scale solar farms. Detailed flow diagrams and performance evaluations are included to demonstrate the system's effectiveness and reliability in real-time applications. Compared to existing monitoring solutions, this system offers lower costs, higher scalability, and enhanced real-time data processing capabilities, making it suitable for deployment in various renewable energy environments.
When dealing with the Internet of Things (IoT), especially industrial IoT (IIoT), two manifest challenges leap to mind. First is the massive amount of data streaming to and from IoT devices, and second is the fast pac...
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