Automatic Identification Technology Research Articles

MONITORING OF PRODUCTION PROCESSES OF RAILWAY TRANSPORT ENTERPRISES

The publication proposes a monitoring technology for production automation based on automatic identification technologies, which will allow real-time monitoring of the progress of technological processes, ensure interdepartmental logistics, as well as perform access and identification security functions in production. On the example of one of the carriage depots, typical shortcomings of the organization of the production process, accounting and identification of parts of a railway transport enterprise are considered. The ways and stages of implementation of automatic identification technologies are proposed, in particular, it is indicated that it is advisable to introduce a system for monitoring production processes of railway transport enterprises in stages, starting with bar-coding technologies. The process of monitoring railway transport enterprises, the interaction of subjects and objects of the production process is disclosed in detail.

Assessing the potential for deep learning and computer vision to identify bumble bee species from images

Pollinators are undergoing a global decline. Although vital to pollinator conservation and ecological research, species-level identification is expensive, time consuming, and requires specialized taxonomic training. However, deep learning and computer vision are providing ways to open this methodological bottleneck through automated identification from images. Focusing on bumble bees, we compare four convolutional neural network classification models to evaluate prediction speed, accuracy, and the potential of this technology for automated bee identification. We gathered over 89,000 images of bumble bees, representing 36 species in North America, to train the ResNet, Wide ResNet, InceptionV3, and MnasNet models. Among these models, InceptionV3 presented a good balance of accuracy (91.6%) and average speed (3.34 ms). Species-level error rates were generally smaller for species represented by more training images. However, error rates also depended on the level of morphological variability among individuals within a species and similarity to other species. Continued development of this technology for automatic species identification and monitoring has the potential to be transformative for the fields of ecology and conservation. To this end, we present BeeMachine, a web application that allows anyone to use our classification model to identify bumble bees in their own images.

A Simulation for Managing Retail Inventory Flow Using RFID and Bar Code Technology

ABSTRACTThe increasingly complex retail environment faces many inventory management challenges. Automatic identification and data capture (AIDC) technologies have been applied by retailers to address these challenges, with mixed levels of success. This article presents a classroom simulation of a retail environment in which students utilize a bar code scanner and a radio frequency identification (RFID) reader to manage inventory for the simulated retailer. From the simulation, students gain hands‐on experience with these technologies, learn about the advantages and disadvantages of the technologies, and discuss additional cutting‐edge AIDC technology.

A vehicle-by-vehicle approach to assess the impact of variable message signs on driving behavior

Variable Message Signs (VMS) provide real-time information on traffic conditions, making it possible to guide drivers through electronic signs along the road. Relevant literature has proved VMS to be effective, especially for diverting traffic during incidents in the highway or inducing a speed reduction. Previous efforts, however, usually involve off-highway experiences, including the use of simulators or stated preference surveys, or the measurement of aggregate values of traffic through technologies that are prone to a higher failure rate, such as loop detectors. For bridging this gap, in this research, we propose a novel vehicle-by-vehicle approach (VBV), that differentiate by vehicle type, to assess the impact of VMS on drivers’ road behavior patterns along a section of a Chilean urban highway during risky situations. In addition to the messaging information, we use full traffic data obtained from free-flow gates equipped with automatic vehicle identification (AVI) technology. We conduct statistical analyses to study two potential messaging-induced behavioral changes, namely speed reduction and lane changes. For the speed reduction behavior, in 87.50% of the studied messages, the results indicate that the messages failed to induce the desired change in behavior. This value decreases to 71.85% for lane changes. The results indicate that heavy vehicle drivers and low-mileage drivers are more likely to follow lane change messages.

A novel design of surface acoustic wave‐based chipless radio frequency identification tag based on multiphysics modeling

AbstractRadio frequency identification (RFID) technique is a kind of wireless, automatic identification technology that is being widely used. Compared to other identification methods such as bar code and two‐dimensional code (quick response code or QR code), the RFID technique has several remarkable merits, such as long reading distance, strong penetrating ability, pollution resistance, high reading efficiency, small size, and large information storage. However, the technique involves high cost and cannot be accepted by cost‐sensitive commodities or applications. To reduce its cost, chipless RFID tags were proposed in recent years using surface acoustic wave (SAW) to read and store the information is one such RFID tags. The tags feature small size, high flexibility, strong radiation resistance, high consistency and repeatability, as well as high temperature stability. In this paper, we propose a novel design for the SAW‐based RFID tags by using the commercial software COMSOL and analyze the performance of SAW tags with different structures.

A security protocol of RFID communication system based on password authenticated with provable security

Radio frequency identification (RFID) technology is a non-contact automatic identification technology. However, due to the limitations of RFID equipment, RFID technology still has hidden safety hazards that cannot be ignored. This paper presents the security architecture of RFID system based on trust chain. According to the RFID system level, the RFID equipment is layered and safely managed to construct a model that directly proves the authenticity of the logo without the need for third-party certification. A new access authentication protocol and a security association protocol supporting fast handover are proposed. Aiming at the privacy leakage of label ownership transfer, a privacy protection model for label ownership transfer is proposed. A prototype protocol for label ownership transfer based on public key encryption is presented. The results show that the prototype protocol meets the label privacy protection and is suitable for tags that support public key encryption.

The Supply Chain Financial Supervision Mechanism of the Internet of Things Based on the Integration of RFID and Wireless Sensor Network

Based on the fusion of wireless sensor modules and UHF RFID readers, this paper develops a UHF RFID reading and writing system based on wireless sensing technology and designs a communication interface circuit that integrates wireless sensing and RFID technology. The financial supervision mechanism of the Internet of Things compatible with these two technologies improves the communication distance limitation of the RFID system and improves the flexibility of the RFID reading and writing system. Secondly, in view of the security issues of WSN small and medium data distribution, this paper proposes a lightweight small data supply chain financial supervision program. The solution adopts two‐way authentication technology based on the improvement of the Internet of Things supply chain, the negotiation of the Internet of Things supply chain, and a lightweight encryption algorithm, which realizes the secure communication between ordinary nodes and gateway nodes, and can more effectively solve the problem of small and medium data distribution in WSN to resist the deficiencies of the financial supervision mechanism; compared with existing solutions of the same magnitude, it has higher security and efficiency. Experimental simulation shows that an important problem in the converged network is the imbalance of node energy consumption. In order to reduce the negative impact of the imbalance of energy consumption on the network, this article compares the two for direct transmission protocol and minimum energy multihop routing protocol. From the perspective of supply chain process performance, based on the proposed technical impact framework, it analyzes how companies actually carry out ID application work, making the research from general to individual, from theory to practice. The network energy consumption calculation method under this protocol improves an improved network architecture model that increases the communication scale. The test results show that the technical impact analysis framework established in this article based on the theory of the Internet of Things and the advantages of RFID technology can analyze the automation benefits, information benefits, and transformative benefits brought by automatic identification technology to the supply chain and introduce complementary resources and potential factors. It provides a theoretical basis and operation method for measuring the impact of RFID on the performance of the financial supervision process based on the Internet of Things supply chain in practical applications.

Critical risk considerations in auto-ID security: Barcode vs. RFID

Automated identification (auto-ID) has been widely used in practice for more than five decades, beginning with the commercial use of barcodes in the early 1970s. More recently, since about 2003, RFID (Radio Frequency IDentification) use has seen widespread adoption. While these automated identification technologies help improve convenience, effectiveness, and efficiency, associated vulnerabilities need to be carefully considered to weigh their advantages against their disadvantages. By its very nature, automated identification has the potential to expose its subject to privacy and security risks. We consider specific vulnerabilities that are associated with barcode and RFID to identify related attack scenarios and discuss means to address such risks and attacks.

Research on automatic defect identification technology of electronic components

Aiming at the problems of low efficiency and low accuracy caused by manual defect detection of electronic components, FCN, SegNet/DeconvNet and DeepLab and other deep learning technologies are studied. Using Caffe, Keras, PyTorch and other frameworks, an automatic defect identification system for electronic components is developed to distinguish qualified products from unqualified ones, so as to realize intelligent defect detection of electronic components. At the same time, the detection accuracy rate is greatly improved, and the quality of electronic components is guaranteed.

Knowledge-Based Decision Support in Healthcare via Near Field Communication.

The benefits of automatic identification technologies in healthcare have been largely recognized. Nevertheless, unlocking their potential to support the most knowledge-intensive medical tasks requires to go beyond mere item identification. This paper presents an innovative Decision Support System (DSS), based on a semantic enhancement of Near Field Communication (NFC) standard. Annotated descriptions of medications and patient’s case history are stored in NFC transponders and used to help caregivers providing the right therapy. The proposed framework includes a lightweight reasoning engine to infer possible incompatibilities in treatment, suggesting substitute therapies. A working prototype is presented in a rheumatology case study and preliminary performance tests are reported. The approach is independent from back-end infrastructures. The proposed DSS framework is validated in a limited but realistic case study, and performance evaluation of the prototype supports its practical feasibility. Automated reasoning on knowledge fragments extracted via NFC enables effective decision support not only in hospital centers, but also in pervasive IoT-based healthcare contexts such as first aid, ambulance transport, rehabilitation facilities and home care.

Research on the Construction of Logistics Information Platform for Coastal Ports under the Background of Electronic Commerce

Guo, B., 2020. Research on the construction of logistics information platform for coastal ports under the background of electronic commerce. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp.120-122. Coconut Creek (Florida), ISSN 0749-0208.The construction of e-commerce integrated information platform is the key to realize the informatization, individuation, high efficiency and sustainable development of port logistics park (Buntak et al., 2019). With the improvement of China's economic strength, many modern technologies, such as automatic identification technology and bar code technology, have been widely applied in the field of port logistics, making ports gradually develop from traditional labor-intensive to e-commerce of logistics operation mode. E-commerce, with its good information processing and transmission system, has become a very important condition for the logistics industry to provide good services. The realization of port logistics informatization is an inevitable requirement to enhance the comprehensive competitiveness of port logistics in the era of e-commerce. Without the guarantee of a perfect logistics system, e-commerce activities cannot be carried out smoothly. This paper discusses the development trend of coastal port logistics in the e-commerce environment and the competitiveness of e-commerce to enhance port logistics. On this basis, the conditions for the construction of port logistics information platform are described.

Investigation of Sustainable Geopolymer Composite Using Automatic Identification Technology

Geopolymers are materials prepared from alkaline-activated cement without a calcium constituent. They are synthetic materials based on aluminosilicates. The main advantage of these environmentally friendly materials is that they save mineral resources and due to being free of calcium constituents, and only a small amount of CO2 emissions are released into the environment. The circular economy model of sustainable development of new composite materials will ensure the competitiveness of industries, their stable economic growth, and a healthy environment. This paper aims to investigate geopolymer composite materials that were reinforced with a mixture of glass powder from recycled windscreens. The glass 100% circulates in the closed material cycle and can be used again in the manufacturing process without any loss of quality. We are focused on verification of readability of selected automatic identification technology and their usability directly in the manufacturing process of geopolymer composite materials.

Studying the state of readiness of institutions and units of medical supply of the armed forces of Ukraine for the implementation of logistics information system

The problem of implementing an information system to implement effective logistic management of streaming processes in the medical service of the Armed Forces of Ukraine and gaining functional compatibility with the medical services of the Armed Forces of the NATO member countries is relevant and requires detailed study.
 The aim of the work is study of the state of readiness of institutions and units of medical supply of the Armed Forces of Ukraine for the implementation of the logistics information system by expert survey.
 The analysis of domestic and foreign scientific literature, the current regulatory framework of Ukraine, the results of the expert survey was conducted to achieve the aim of the study. During the research, methods of information retrieval, systematization, content analysis, expert survey, comparison, generalization, mathematical-statistical and graphical modeling were used.
 The article analyzes the results of an expert survey on certain aspects of the practical implementation of information logistics in managing the medical supply of the Armed Forces of Ukraine. The experts were medical servicemen and employees of the Armed Forces of Ukraine, who are involved in the medical supply system of the troops. The analysis showed that currently the documents of the movement and accounting of medical supplies in institutions and units of medical supply of the Armed Forces of Ukraine is carried out both in paper and electronic format. Experts noted that for certain forms there is a duplication of documents, so the extra time is used. At those workplaces where paper work takes place (45%), there are no computers at all. Computers located at expert workplaces are connected to local networks or have Internet access only in 48% of respondents. It is established that in the functioning of institutions and units of the medical supply of the Armed Forces of Ukraine there is not automatic identification technology – RFID. It was found that 79% of respondents lack professional automated control systems (ACS). Some institutions and units of the medical supply of the Armed Forces of Ukraine have an automatic control system «Dnipro». However, it is emphasized that computers and ACS are unstable.
 An analysis of the results of the expert survey made it possible to determine that the primary task in the context of introducing the logistics information system is to provide modern computer equipment for the institutions and units of the medical supply of the Armed Forces of Ukraine. At the same time, there is a need to increase the level of skills in working with computer equipment of the personnel of the medical supply system of the Armed Forces of Ukraine, who are involved in using computer technologies. The need for the development of modern decision support software for managing streaming processes in the medical supply system of the Armed Forces of Ukraine is established.
 As well as the introduction of a program for the automatic accounting of medical supplies, which will be synchronized with the Medical Forces Command, institutions and medical supply units of the Armed Forces of Ukraine. At the same time, the specified software should have a single interface with the Armed Forces of NATO member states.

Amur tiger stripes: individual identification based on deep convolutional neural network.

The automatic individual identification of Amur tigers (Panthera tigris altaica) is important for population monitoring and making effective conservation strategies. Most existing research primarily relies on manual identification, which does not scale well to large datasets. In this paper, the deep convolution neural networks algorithm is constructed to implement the automatic individual identification for large numbers of Amur tiger images. The experimental data were obtained from 40 Amur tigers in Tieling Guaipo Tiger Park, China. The number of images collected from each tiger was approximately 200, and a total of 8277 images were obtained. The experiments were carried out on both the left and right side of body. Our results suggested that the recognition accuracy rate of left and right sides are 90.48% and 93.5%, respectively. The accuracy of our network has achieved the similar level compared to other state of the art networks like LeNet, ResNet34, and ZF_Net. The running time is much shorter than that of other networks. Consequently, this study can provide a new approach on automatic individual identification technology in the case of the Amur tiger.

Rancang Bangun Traffic Light System Tanggap Darurat Berbasis IoT

At crossroads, both crossing three and crossing four which have traffic lights, there is often heavy traffic. Of course this can hamper the performance of priority vehicles that will cross the intersection. To overcome this, the researchers designed a traffic light microcontroller system using a sound sensor. Sound sensor is an automatic identification technology that uses sound waves that hit the sensor membrane which causes the sensor membrane to move which has a small coil behind the membrane up and down then the sensor will be connected to the lights at each airport parking road junction so that the traffic lights of the parking area and arrival terminal or the release changes automatically. The purpose of this study is expected to produce a traffic light system design that utilizes IOT sound sensor technology to the density of vehicles that are at a crossroads either intersection three or intersection four in order to regulate the smooth flow of vehicles and things emergency vehicles (ambulances, fire engines or officials) can work on time and at the maximum, The output produced is a prototype IoT product and publication to journal

Development of an identifier analysis algorithms to account for the movement of material flow in space transport systems

In modern space transport systems, the extremely urgent task of a unified identification and labeling of goods for various segments. One of the main tasks to be solved in the process of organizing the movement of cargo for delivery to the International Space Station is the organization of operational management. The article discusses international standards for identification and hardware implemented on the basis of radio frequency identification technology. The cargo movement system should have modules for cargo traffic planning, which is currently not the case. In addition, an important task in organizing the operational accounting of the material flow of goods is the realization of the possibility of a single information exchange between the various segments of the space system, which in turn involves the use of standardized methods and means. The article discusses the technology of automatic identification in relation to the space industry, the basic standard documents and provides a new developed algorithm for the analysis of identification codes of cargo data for the space transport system.

Survey on negative line loss rate of transformer region: Rectification measures and challenges

The system architecture and method for monitoring and statistical analysis of the line losses of the transformer region are introduced. The statistical method for the current system is adopted to determine the functional relationship between the statistical line loss, statistical line loss rate, and gateway power supply of the transformer region. Moreover, the trend of the parameters in a typical residential area is analyzed. Based on the analysis, the three reasons for the formation of transformer regions with a reasonable rate of line loss and the measures for the unreasonable rates are summarized. It is recommended that the line loss monitoring and analysis system should include the functions of approval, examination, and verification, as well as automatic identification. The transformer region without any abnormality in the line loss should be exempt from the review. For the transformer region with a residential elevator, however, the statistical rules should be modified to calculate the actual line loss rate. Finally, the challenges in the management of the transformer region with a negative line loss rate are presented. It is concluded that the application of transformer–customer relationship automatic identification technology and artificial intelligence abnormality diagnosis can significantly improve the efficiency of line loss management.

Secured e-payment system based on automated authentication data and iterated salted hash algorithm

Electronic payment has been considered as one of the most significant and convenient applications of modern electronic services e-University compared to traditional methods that impose time-consuming, human resources, and inefficiency. Different automatic identification technologies have been widely used, such as radio frequency identification (RFID). Extensive research and several applications are focusing on taking the maximum advantage of RFID technology. Data and information security had considered a crucial role when information concerning e-commerce, e-banking, or e-payments, especially due to it required real data to establish accessed illegally. Hence, data originality and security fall a very significant and critical issue in data communication services in recent years. Applications such as e-banking or e-commerce regularly contain sensitive and personal information that should be managed and controlled by authorized persons. Thus, keeping a secure password is important to prevent unauthorized users from illegal access. The password hashing is one of the safety methods and means of preventing attacks. In this article, focuses on proposing an RFID based electronic payment and also provide multi-level security privileges for an academic domain by using RFID technology besides the programmable logic circuit as well the system used VB.Net C# environment also desktop and web-based application for system working purposes. The proposed system aims to manage student payments in a secure manner and provides the capabilities of getting a bus ticket, copying books, buying food, paying registration fees, and other services. The results have shown the system is secured by using the confirmation code in addition to password encryption.

Adapted RFID anti-collision algorithm and its application in sharing economy

In recent years, the sharing economy has developed vigorously, and the internet of things (IoT) technology is an important technology to realise the sharing economy. As an automatic identification technology, radio frequency identification (RFID) technology is the key technology to build the internet of things and an essential part of the sharing economy. In order to solve the collision problem of tags identification, an improved grouping adaptive query tree algorithm (IGAQT) is proposed in this paper. Compared to the most of existing anti-collision algorithms, simulation results show that our proposed algorithm can achieve better performance in terms of time complexity and communication overload. And the algorithm is applied to the actual case of sharing economy.

Research on Wear Recognition of Electric Worker’s Helmet Based on Neural Network

Head injury is an important cause of electric construction accidents. Wearing a safety helmet is an effective measure to prevent electric construction accidents, and in the work, unsafe behavior of workers without wearing a helmet often occurs. This paper proposes a neural network-based automatic cap wear automatic identification and detection technology to identify the behavior of unwearing helmets in power construction. In view of the shortcomings of the existing helmet detection scheme in the complex environment, such as low efficiency and low recognition accuracy, this paper selects the region of the neural network (Fast-er-RCNN) to identify the wearing of the helmet during the power operation. The overall scheme uses the target detection scheme based on the foreground detection technology to detect the target individual in the obtained video recording of the power operation. The Kalman filter algorithm is used to track the target in the video and solve the occlusion problem in the video image. Through the actual detection of power construction monitoring video, the availability and efficiency of the designed algorithm are verified. The target recognition accuracy can reach 85.7% and the recall rate is 87.5%.