Automated Component Detection for Quality PCB Using YOLO Algorithm with IoT Real-Time Streaming on Raspberry Pi

Research Article| March 01, 2016 The Internet of Geophysical Things: Raspberry Pi Enhanced REF TEK (RaPiER) System Integration and Evaluation Frank Sepulveda; Frank Sepulveda aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Search for other works by this author on: GSW Google Scholar Jay Pulliam Jay Pulliam aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Search for other works by this author on: GSW Google Scholar Author and Article Information Frank Sepulveda aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Jay Pulliam aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Publisher: Seismological Society of America First Online: 14 Jul 2017 Online Issn: 1938-2057 Print Issn: 0895-0695 © 2016 by the Seismological Society of America Seismological Research Letters (2016) 87 (2A): 345–357. https://doi.org/10.1785/0220150234 Article history First Online: 14 Jul 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Frank Sepulveda, Jay Pulliam; The Internet of Geophysical Things: Raspberry Pi Enhanced REF TEK (RaPiER) System Integration and Evaluation. Seismological Research Letters 2016;; 87 (2A): 345–357. doi: https://doi.org/10.1785/0220150234 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietySeismological Research Letters Search Advanced Search ABSTRACT The proliferation of commercial Internet of Things (IoT) devices is raising consumers’ awareness of the benefits of enhancing everyday objects with the ability to communicate, sense, and process information. Commercial‐off‐the‐shelf (COTS) versions of the embedded technologies responsible for the rise of the IoT are easy‐to‐use, inexpensive, and relatively powerful. IoT Makers, technological do‐it‐yourself enthusiasts, utilize these technologies and the IoT ecosystem to create IoT devices that range from casual hobbyist to entrepreneurial in nature.In an effort to develop a “no‐engineer‐needed” Internet of Geophysical Things (IoGT) device, we integrated a COTS embedded computer with a geoscience‐related COTS data acquisition system (DAS). Using skills common to geoscientists, we integrated the Raspberry Pi System‐On‐Chip with the REF TEK (a Trimble brand) 130‐01 DAS. This Raspberry Pi enhanced REF TEK (RaPiER) provides IoGT Makers a platform for the development of geoscientific sensor node or network enhancements. IoGT Makers can use the RaPiER to tinker with IoT capabilities while simultaneously acquiring research‐quality data. Geoscientific (i.e., seismic) application areas that may benefit from RaPiER, particularly RaPiER nodal processing, include earthquake and engineering seismology.In this article, we discuss the emerging technologies that allow IoGT Makers to build their own IoGT device. We review our selection of the Raspberry Pi and REF TEK 130‐01 for IoGT device integration. We provide a RaPiER system integration guide and REF TEK interface software compiled for the Raspberry Pi ( available in the electronic supplement to this article). We present methods to expand RaPiER capabilities using the Raspberry Pi’s ecosystem. Last, we discuss our evaluation of RaPiER’s performance and its suitability for realistic field deployments. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

Flexible electronics and sensors are a key enabling element for the realization of wearables and geometry adaptive devices needed to follow current trends such as the Internet of things or Industry 4.0. Within this paper, we present a new and flexible packaging platform by the fabrication of an ultra-thin and highly flexible printed circuit board (PCB).The thermoplastic polymer Parylene, which combines a variety of unique properties such as optical transparency, biostability and biocompatibility according to ISO 10993, thermal stability as well as low permeability for gases and water, was used as the base for the new PCB.Particularly, its mechanical properties, especially the absence of intrinsic stresses, as well as its low Young’s modulus and good bendability are advantageous when using Parylene films as a free-standing substrate for flexible applications. The chemical inertness of Parylene against all common acids, bases and solvents ensures its compatibility with established standard microsystem technologies.For the realization of ultra-thin flexible PCBs, Parylene was used as a substrate as well as for the encapsulation and protection layer, respectively. Furthermore, Parylene was the dielectric between the metallic conductive layers. These redistribution layers (RDL) were deposited and patterned by standard microsystem technologies, such as sputtering, lithography and wet chemical etching. Hence, structure sizes of down to 10 µm were successfully realized. Different metals, such as gold, copper, and aluminum were tested for the RDL. Alternatively, printing technologies such as screen printing and aerosol jet printing were successfully demonstrated for the if conductive silver layerse. The electrical connection between the various RDL was of special interest throughout the study and was realized by etching vertical vias through the Parylene using oxygen plasma. Due to the low total thickness of the flexible Parylene PCB of 20 µm or even less, the obtained vias through the Parylene feature an advantageous low aspect ratio. For the contact formation through the vias, different methods were investigated, e. g. sputtering, printing and electrochemical deposition.Finally, the fabricated flexible Parylene PCB were characterized with respect to their bendability and electrical properties. Doing so, the resistivity and capacitance were measured as well as the frequency response between 20 kHz and 500 MHz. Particularly, for frequencies below 1 MHz the realized flexible Parylene PCBs show a good electrical performance.A third function of Parylene with respect to the realization of an ultra-thin and flexible PCB is its usage as a barrier or capping layer. Doing so, new approaches such as embedding electronic or sensor components in the flexible PCB can be enabled. Other integration technologies such as wire bonding, printing or gluing were investigated with respect to their usability for the new flexible PCB as well. Besides, also the direct fabrication of sensors on the Parylene flexible PCB was successfully demonstrated by the realization of a flexible potentiometric pH sensor.The presented new type of ultra-thin PCB is a versatile platform for the realization of flexible electronics, sensors and devices. Due to its biocompatible properties, the flexible Parylene PCB can be used for medical applications but also for the integration of MEMS, chemical sensors and optical components, respectively. Doing so, it enables the realization of smart systems for wearable applications and their integration into light weight constructions. Within this paper, the concept of this new approach, the respected fabrication and integration technologies as well as possible applications are presented in detail. Figure 1

Printed Circuit Boards (PCBs) are widely used in most electronic devices. Typically, a PCB design has a set of components that needs to be assembled. In a broad sense, this assembly task involves placing PCB components at designated location on a PCB board; fixing PCB components; and testing the PCB after assembly operation to ensure that it is in proper working order. The stringent requirements of having a higher component density on PCBs, a shorter assembly time, and a more reliable product prompt manufacturers to automate the process of PCB assembly. Frequently, a few placement machines may work together to form an assembly line. Thus, the application of more than one machine for component placement on a PCB presents a line-balancing problem, which is basically concerned with balancing the workload of all the machines in an assembly line. This paper describes the application of a new artificial intelligence technique known as the immune algorithm to PCB component placement as well as the line balancing of PCB assembly line. It also includes an overview of PCB assembly and an outline of the assembly line balancing problem. Two case studies are used to validate the IA engine developed in this work. The details of IA, the IA engine and the case studies are presented.

In today's world, Internet of Things (IoT) technology has revolutionized various fields – including agriculture – by offering smart solutions that enhance crop yield and quality. One crucial aspect of smart farming is the application of IoT for disease detection and prevention. Crop diseases caused by bacteria and viruses can have devastating effects, leading to significant financial losses for farmers. Early detection plays a crucial role in managing these diseases, and IoT technology provides reliable and efficient methods to achieve this goal. To aid in the research on disease recognition in corn or maize plants, a large-scale dataset comprising 4188 images across four disease categories – namely, healthy, common rust, gray-leaf spot, and blight – is utilized. This dataset is used to train various machine learning algorithms such as K-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), decision tree (DT), convolutional neural network (CNN), naïve Bayes (NB), gradient boosting trees (GBT), long short-term memory (LSTM), and the algorithms from recent literature such as genetic algorithm-based ensemble classifier, XGBoost, AdaBoost and XGBoost + KNN to accurately identify disease patterns in plants and is loaded into the Raspberry Pi. By interfacing a camera with a Raspberry Pi, leaf diseases can be detected, and the farm’s status can be sent to the farmer’s webpage using a Wi- Fi server. This information empowers farmers to take immediate action to control the disease such as activating sprinklers or applying pesticides. Through manually controllable on/off mechanisms, farmers can remotely manage these actions, ensuring the health and disease-free state of their crops. Among the selected algorithms, the XGBoost + KNN algorithm demonstrates the highest accuracy, reaching an impressive 98.77%.

Purpose– The purpose of this paper is to examine the role of capability and alliance arising from the internet of things (IoT), specifically in the relationships between strategic orientations (entrepreneurial and market foci) with product and process innovations. In addition, it investigates the direct relationship between IoT capability and alliance. Improving these relationships assist in ensuring that new knowledge from the IoT can be translated into tangible business innovations that contribute to economic development.Design/methodology/approach– Data from 207 new high-technology IoT ventures in China were obtained after three-wave mailing (i.e. two reminders). Following a rigorous process to purify and validate the measurement scale items, the study used structural equation modeling to test the conceptual model.Findings– Findings demonstrate that an IoT capability only enhances product innovation, however, with the addition and support from IoT alliance, both product and process innovation can be achieved in new high-tech IoT ventures. This nuanced insight suggests that new high-tech IoT ventures should focus on building their IoT capability, and at the same time, develop IoT alliances with value chain partners in order to fully take advantage of IoT and gain a better position to formulate more novel offerings.Originality/value– The study is first to contribute with a much needed framework of IoT and entrepreneurship by examining the role of IoT capability further in the relationships between: entrepreneurial orientation and market orientation with product and process innovations arising from IoT; and the role of IoT alliance (interfirm relations, partnerships, etc.) on the relationship above.

An innovative approach is described for diagnosing faults in printed circuit boards (PCB) and PCB components through the detection, analysis, and localization of electrical field changes that occur within and around the PCB. This method utilizes electromagnetic emissions (EME) originating from the PCB to determine circuit health. EME from rapidly changing voltages and currents within high-speed logic and other circuits have traditionally been seen as a problematic source of interference that must be eliminated to as great an extent as possible. However, changes within these emissions can be a highly significant indicator that a failure has occurred within a PCB component as well as within adjacent circuit card paths of the board itself. Further, the hardware and software requirements needed to capture and analyze these emissions are relatively simple in comparison to todaypsilas highly complex automatic test equipment. This unique approach involves analyzing electromagnetic emission signatures through automated means, and ascribing failures to the circuit board as a whole, as well as to the individual circuit board components.

Major advances in the Internet of Things (IoT) technologies are offering unprecedented automated services to various sectors. IoT has shown great promise in transforming buildings and institutions into smart buildings and institutions, making traditional task management more efficient. In particular, there has been remarkable progress in successfully integrating IoT into various contexts, such as smart homes, businesses and cities. Success in such technological transformations is not only due to the proper deployment and implementation of IoT but also to the effective employment of related technologies, such as big data and cloud computing technologies, and making informed decisions on the inclusion of the required hardware and software for all the elements involved in the IoT environment. While a significant amount of IoT research in various contexts has been proliferated in recent years, attention given to its deployment for linguistic landscapes (LLs) is still very rare. The aim of this paper is to propose a smart Al-Noor Mall LL which takes into account the appropriate deployment of IoT tools and relevant technologies. The paper also thoroughly discusses the background of the field, covering IoT technologies, cloud computing, and big data studies, followed by a review of the recent publications involving the successful deployment of IoT technologies combined with big data and cloud computing in various contexts. The literature also covers the success factors that contribute to the robustness of the required real-time operating system (RTOS) in an IoT-based environment in order to enable IoT devices to manage their resources efficiently. Based on a detailed analysis of the literature, a three-level framework (i.e. the object, communications and application levels) together with the elements that are required for IoT-based smart LL solutions is proposed. A case study of Al-Noor Mall is used to validate the proposed framework and the results indicate that IBM Bluemix can help Al-Noor Mall management and customers to locate any particular shop in the huge shopping mall, which thereby makes the customers’ shopping experience more satisfying. Finally, the challenges (i.e. energy efficiency, security, and intelligent data analysis) facing the successful deployment of IoT technologies are discussed with proposals for future research directions in the IoT research field.

The idea to connect everything to anything and at any point of time is what vaguely defines the concept of the Internet of Things (IoT). The IoT is not only about providing connectivity but also facilitating interaction among these connected things. One of the most significant concerns of IoT is to provide security assurance for the data exchange because data is vulnerable to some attacks by the attackers at each layer of IoT. The IoT has a layered structure where each layer provides a service. The security needs vary from layer to layer as each layer serves a different purpose. This paper aims to analyze the various security and privacy threats related to IoT. Some attacks have been discussed along with some existing and proposed counter measures. In developing countries, IoT technologies have brought increased efficiency and effectiveness to existing processes. For instance, farmers are using remote sensors to monitor moisture levels and soil conditions in the fields to avoid crop failure. Similar sensors are providing remote control of micro-irrigation pumps for example in India and water pumps in Rwanda, improving functionality and reducing repair intervals. And in Haiti, healthcare professionals are using “smart” thermometers to better track vaccine delivery and storage. Totally the paper presents an overview of the enablement of IoT in developing countries and discusses the visions, general applications, opportunities and challenges of IoT in these countries. It also touches on issues relating to security, privacy, trust and the accompanied complexity. The potential applications for IoT are countless and can optimize processes with a direct impact on society. Certain challenges have to be addressed to make IoT deployment successful. It will be shown that some of the challenges can be turned into opportunities and that IoT has good chances to succeed in developing countries. This report explores the current use and potential of Internet of Things (IoT) technologies in tackling global development challenges, highlighting a number of specific instances where IoT interventions are helping to solve some of the world’s most pressing issues it presents summary conclusions on what is required for the IoT to reach billions of people living in the developing world, and also to accelerate income growth and social development as a result.

The research object in the work is the printed circuit boards (PCB) Production technological process using the additive technology of photopolymer 3D printing. The existing problem is that the manufacturing process of single-sided and double-sided PCBs, simple in technology, from the third to the fifth accuracy class, requires the use of a large amount of consumables and technological equipment. In turn, this affects the cost of the product. The research subject is models and methods for manufacturing PCB using photopolymer 3D printing. In order to reduce the cost of materials: film or aerosol photoresist, as well as reduce the number of technological operations, applying photoresist and for the manufacture of PCBs stencils, it is proposed to use photopolymer 3D printing technologies for the manufacture of PCBs. The paper analyzes the costs of Plexiwire Resin Basic Orange Transparen photopolymer resin for the manufacture of single-sided PCBs and calculates the cost of the consumable (resin) compared to the costs of dry film photoresist. 60 % cost of consumables (photopolymer resin) compared to dry film photoresist for making single-sided PCBs. The work is aimed at determining the dependence of the geometric dimensions of the PСВs topology and the consumption of photopolymer resin on the technological parameters of photopolymer exposure. A regression correlation model of the dependence of resin consumption on exposure parameters has been developed and correlation coefficients have been calculated. It has been established that with an increase in the exposure time of the photopolymer resin, the consumption of the photopolymer resin increases and the deviation of the geometric dimensions of the PCBs topology increases, which in turn negatively affects the quality of the product. Therefore, using the obtained regression model, it is possible to calculate the influence of parameters on the PCB topology and reduce the deviation of conductor sizes and resin consumption.

Printed circuit boards (PCBs) are primarily used to connect electronic components to each other. It is one of the most important stages in the manufacturing of electronic products. A small defect in the PCB can make the final product inoperable. Therefore, careful and meticulous defect detection steps are necessary and indispensable in the PCB manufacturing process. The detection methods can generally be divided into manual inspection and automatic optical inspection (AOI). The main disadvantage of manual detection is that the detection speed is too slow, resulting in a waste of human resources and costs. Thus, in order to speed up the production speed, AOI techniques have been adopted by many PCB manufacturers. Most current AOI mechanisms use traditional optical algorithms. These algorithms can easily lead to misjudgments due to different light and shadow changes caused by slight differences in PCB placement or solder amount so that qualified PCBs are judged as defective products, which is also the main reason for the high misjudgment rate of AOI detection. In order to effectively solve the problem of AOI misjudgment, manual re-judgment is currently the reinspection method adopted by most PCB manufacturers for defective products judged by AOI. Undoubtedly, the need for inspectors is another kind of labor cost. To reduce the labor cost. of manual re-judgement, an accurate and efficient PCB defect reinspection mechanism based on deep learning algorithm is proposed. This mechanism mainly establishes two detection models, which can classify the defects of the product. When both models have basic recognition capabilities, the two models are then combined into a main model to improve the accuracy of defect detection. In the study, the data provided by Lite-On Technology Co., Ltd. were implemented. To achieve the practical application value in the industry, this research not only considers the problem of detection accuracy, but also considers the problem of detection execution speed. Therefore, fewer parameters are used in the construction of the model. The research results show that the accuracy rate of defect detection is about 95%, and the recall rate is 94%. Compared with other detection modules, the execution speed is greatly improved. The detection time of each image is only 0.027 s, which fully meets the purpose of industrial practical application.

In today's era, when technology is growing rapidly, the Internet of Things (IoT) is a technology having massive applications, which are employed in various domains. Similarly, the Healthcare Internet of Things (IoT) applies IoT to the healthcare industry. The IoT is indeed a networked platform comprising connectable devices that can acquire, transfer, and store data without human or computer intervention. The IoT promises a plethora of benefits for refining and improving healthcare delivery, including the potential to diagnose, examine, and cure the patient. It reduces the need for human intervention while also allowing for the early diagnosis of health hazards. It is becoming equally important to consider how existing, as well as upcoming, IoT technologies might help healthcare systems provide therapeutic benefits. The goal of this chapter is to provide an understanding of recent IoT in healthcare and to illustrate how the Internet of Things devices are boosting healthcare delivery and how IoT technology may revolutionize and disrupt global healthcare in the coming decade. Healthcare IoT capabilities are additionally investigated in order to theorize how IoT might assist us in moving away from our existing different levels of health systems towards a more integrated, progressive, and continuous approach. Patient care may be ensured on time, and with on-time assistance, treatment expenses can be decreased, and therapies can be made more effective by employing IoT in healthcare practitioners. From smartwatches to cancer care, smartwatches are used to monitor one's health and wellbeing. Finally, this chapter will look into potential concerns with IoT, such as impediments to market acceptability from healthcare providers and consumers, interoperability, security and privacy, remuneration and standardization, information storage, and control and ownership. Policy support, cybersecurity-focused guidelines, rigorous strategic planning, and open policies will be critical enablers of IoT in contemporary healthcare within healthcare organizations. IoT has a lot of potential for enhancing the efficiency of the healthcare system and societal well-being.

Smart city is a city that increases the interactivity of its components and put emphasis on their functionality. Internet of Things technology (IoT) is an innovative solution in environmental protection. Usually, information on air quality is very scattered. This paper describes the test stages of pre-implementation works, focusing on the presentation of the technical design of the measurement nodes and the assumptions of the IT project. The goal of the project Intelligent Wireless Sensor Network Infrastructure (IIBSC) is, among others, to create a dense network of air quality measurement nodes at city, district or even street level. The concept is based on Internet of Things (IoT) technology using a matrix construction tool connected to multiple identical measurement nodes located in the test area. The project developed a hardware platform supporting sensors and resistant to external factors, and an ISIMPIO information platform based on edge processing technology for processing data from air quality sensors. Due to the use of Internet of Things (IoT) technology, an edge server using edge processing was designed. Edge server provides a complete ecosystem for building edge applications that are fully optimized for seamless field work. In addition, it allows the implementation of integrated Python software, the MQ Telemetry Transport support protocol (MQTT), time-series database, firmware update over a wireless network, and built-in security system. Measuring the concentration of particulate matter and other substances in the air will be useful for specialists assessing their dynamics. The technology and test installation selected corresponds to the leading solutions in this field in Europe and, in the future, should also be extended to less urbanised areas.

The Internet of Things (IoT) is a technology and plays a key role in just this process. In designing better cities,embedded devices include this new technology, which the internet is similar to everybody. IoT solutions are spread through different regions, such as agriculture, healthcare, the motor industry, education, and home automation, etc. wireless communication (WC) is now becoming an efficient role for incorporating wireless communicationenvironment, computers, organizations, and governments. WC is a budding technology in IoT, and it involves further learning. This dilemma motivates the authors to suggest a standardized IoT WC system. The formation is subdivided into four tiers, according to the IoT architecture. The initial two steps concentrate on the design of Sensors and gateways; cloud integration is identified in the third stage, the server configuration is discussed in the fourth stage, and cloud integration is listed in the third stage user interface is seen in the fifth stage. Proposed, hence, the solution enables the IoT application developer's work. The design using the clean energy consumption case study. Sensors and Raspberry pi are used in the application to quantify and then provide electricity usage using wireless communication between the devices consumed by the home or building. This provides the client with a rising knowledge of the pattern of power consumption and the usage of electricity using Recurrent Neural Network(RNN).

The objective of this study is to investigate the environmental impacts of a printed circuit board (PCB) manufacturing plant through streamlined life cycle assessment approach. As a result, the most effective recommendations on minimizing the environmental impacts for the mentioned sector are revealed and first steps towards establishing a country specific database are taken. The whole PCB production consists of two consecutive stages: namely board fabrication followed by the manufacturing of PCB. Manufacturing of PCB contributes the highest shares to freshwater aquatic ecotoxicity potential (FAETP) and ozone layer depletion potential (ODP). Eighty-nine percent of FAETP is found to be generated from the manufacturing of PCB. Almost all of this contribution can be attributed to the disposal of copper containing wastewater treatment sludge from etching operations to incineration. On the other hand, PCB manufacturing has 73% share in total ODP. Within the manufacturing of PCB, as etching operations are found to be of importance for all the impact categories except eutrophication potential (EP), it is recommended to focus further studies on in-plant control of etching.

The Internet of Things (IoT) technology will soon become an integral part of our daily lives to facilitate the control and monitoring of processes and objects and revolutionize the ways that human interact with the physical world. For all features of IoT to become fully functional in practice, there are several obstacles on the way to be surmounted and critical challenges to be addressed. These include, but are not limited to cybersecurity, data privacy, energy consumption and scalability. The Blockchain decentralized nature and its multi-faceted procedures offers a useful mechanism to tackle several of these IoT challenges. However, applying the Blockchain protocols to IoT without considering their tremendous computational loads, delays, and bandwidth overhead can let to a new set of problems. This review evaluates some of the main challenges we face in the integration of Blockchain and IoT technologies and provides insights and high level solutions that can potentially handle the shortcomings and constraints of both IoT and Blockchain technologies.