Built-in Camera Research Articles

Visfer: Camera-based visual data transfer for cross-device visualization

Going beyond the desktop to leverage novel devices—such as smartphones, tablets, or large displays—for visual sensemaking typically requires supporting extraneous operations for device discovery, interaction sharing, and view management. Such operations can be time-consuming and tedious and distract the user from the actual analysis. Embodied interaction models in these multi-device environments can take advantage of the natural interaction and physicality afforded by multimodal devices and help effectively carry out these operations in visual sensemaking. In this article, we present cross-device interaction models for visualization spaces, that are embodied in nature, by conducting a user study to elicit actions from participants that could trigger a portrayed effect of sharing visualizations (and therefore information) across devices. We then explore one common interaction style from this design elicitation called Visfer, a technique for effortlessly sharing visualizations across devices using the visual medium. More specifically, this technique involves taking pictures of visualizations, or rather the QR codes augmenting them, on a display using the built-in camera on a handheld device. Our contributions include a conceptual framework for cross-device interaction and the Visfer technique itself, as well as transformation guidelines to exploit the capabilities of each specific device and a web framework for encoding visualization components into animated QR codes, which capture multiple frames of QR codes to embed more information. Beyond this, we also present the results from a performance evaluation for the visual data transfer enabled by Visfer. We end the article by presenting the application examples of our Visfer framework.

Developing Iris Recognition System for Smartphone Security

Smartphones have become an important way to store sensitive information; therefore, users’ privacy needs to be highly protected. This can be done by using the most reliable and accurate biometric identification system available today: iris recognition. This paper develops and tests an iris recognition system for smartphones. The system uses eye images that rely on visible wavelength; these images are acquired by the smartphone built-in camera. The development of the system passes through four main phases: the first phase is the iris segmentation phase, which is done in three steps to detect the iris region from the captured image, which contains the eye and part of the face using Haar Cascade Classifier training, pupil localization, and iris localization using a Circular Hough Transform. In the second phase, the system applies normalization using a Rubber Sheet model, which converts the iris image to a fixed size pattern. In the third phase, unique features are extracted from that pattern using a Deep Sparse Filtering algorithm. Finally, in the matching phase, seven different matching techniques are investigated to decide the most appropriate one the system will use to verify the user. Two types of testing are conducted: Offline and Online tests. The BIPLab database and a collected dataset are used to measure the accuracy of the system phases and to calculate the Equal Error Rate (EER) for the whole system. The average EER is 0.18 for the BIPLab database and 0.26 for the collected dataset.

High-Performance Colorimetric Detection of Thiosulfate by Using Silver Nanoparticles for Smartphone-Based Analysis.

Developing thiosulfate (S2O32-) sensors with silver nanoparticles (AgNPs) for analysis of aqueous solutions with the interference of other anions remains challenging. In this study, we propose a new strategy for excellent selective colorimetric detection of S2O32-. The nonmorphological transition of AgNPs leading to a color change from yellow to brown is verified by UV-vis, TEM, DLS, SEM, and XPS analyses. The sensor exhibits high sensitivity with detection limits of 1.0 μM by naked-eye determination and 0.2 μM by UV-vis spectroscopy analysis. The linear relationship (R2 = 0.998) between the (A0 - A)/A0 values and S2O32- concentrations from 0.2 μM to 2.0 μM indicates that the fabricated AgNPs-based colorimetric sensor can be employed for quantitative assay of S2O32-. Colorimetric responses are also monitored using the built-in camera of a smartphone. The sensor shows a linear response to S2O32- in 0-20.0 μM solutions under the optimized conditions and is thus more suitable for rapid on-site tests than other detection methods. A smartphone application (app) is downloaded under Android or IOS platforms to measure the RGB (red, green, blue) values of the colorimetric sensor after exposure to the analyte. Following data processing, the RGB values are converted into concentration values by using preloaded calibration curves. Confirmatory analysis indicates that the proposed S2O32- colorimetric sensor exhibits feasibility and sensitivity for S2O32- detection in real environmental samples.

A smart device application for the automated determination of E. coli colonies on agar plates.

The manual counting of colonies on agar plates to estimate the number of viable organisms (so-called colony-forming units-CFUs) in a defined sample is a commonly used method in microbiological laboratories. The automation of this arduous and time-consuming process through benchtop devices with integrated image processing capability addresses the need for faster and higher sample throughput and more accuracy. While benchtop colony counter solutions are often bulky and expensive, we investigated a cost-effective way to automate the colony counting process with smart devices using their inbuilt camera features and a server-based image processing algorithm. The performance of the developed solution is compared to a commercially available smartphone colony counter app and the manual counts of two scientists trained in biological experiments. The comparisons show a high accuracy of the presented system and demonstrate the potential of smart devices to displace well-established laboratory equipment.

Erratum to: The social essentials of learning: an experimental investigation of collaborative problem solving and knowledge construction in mathematics classrooms in Australia and China

Interactive problem solving and learning are priorities in contemporary education, but these complex processes have proved difficult to research. This project addresses the question “How do we optimise social interaction for the promotion of learning in a mathematics classroom?” Employing the logic of multi-theoretic research design, this project uses the newly built Science of Learning Research Classroom (ARC-SR120300015) at The University of Melbourne and equivalent facilities in China to investigate classroom learning and social interactions, focusing on collaborative small group problem solving as a way to make the social aspects of learning visible. In Australia and China, intact classes of local year 7 students with their usual teacher will be brought into the research classroom facilities with built-in video cameras and audio recording equipment to participate in purposefully designed activities in mathematics. The students will undertake a sequence of tasks in the social units of individual, pair, small group (typically four students) and whole class. The conditions for student collaborative problem solving and learning will be manipulated so that student and teacher contributions to that learning process can be distinguished. Parallel and comparative analyses will identify culture-specific interactive patterns and provide the basis for hypotheses about the learning characteristics underlying collaborative problem solving performance documented in the research classrooms in each country. The ultimate goals of the project are to generate, develop and test more sophisticated hypotheses for the optimisation of social interaction in the mathematics classroom in the interest of improving learning and, particularly, student collaborative problem solving.

Lipopolysaccharides detection on a grating-coupled surface plasmon resonance smartphone biosensor

We report a smartphone label-free biosensor platform based on grating-coupled surface plasmon resonance (GC-SPR). The sensor system relies on the smartphone's built-in flash light source and camera, a disposable sensor chip with Au diffraction grating and a compact disk (CD) as the spectra dispersive unit. The Au grating sensor chip was modified with a synthetic peptide receptor and employed on the GC-SPR detection of lipopolysaccharides (known as endotoxins) with detection limit of 32.5ng/mL in water. Upon incubation of various small and macro-molecules with the synthetic peptide modified sensor chips, we concluded the good selectivity of the sensor for LPS detection. In addition, the sensor shows feasibility for the detection of LPS in commonly used clinical injectable fluids, such as clinical-grade 0.9% sodium chloride intravenous infusion, compound sodium lactate intravenous infusion and insulin aspart. The developed sensor platform offers the advantage of portability and simplicity, which is attractive for point-of-care and remote detection of biomedical and environmental targets.

Noninvasive hemoglobin measurement using unmodified smartphone camera and white flash.

We show that a mobile phone can measure hemoglobin levels using the built-in RGB camera and white LED without modification. Prior work has demonstrated that a smartphone using the built-in RGB camera with the aid of visible and IR lights can achieve a Pearson correlation results between 0.69-0.82 and an RMSE value between 1.26-1.56 g/dL. Our system builds upon the prior work and demonstrates that with only the built-in white LED, the estimation of hemoglobin level has a Pearson correlation of 0.62 with an RMSE of 1.27 g/dL. This extension work demonstrates that it is feasible to measure hemoglobin without using an IR source.

WEAR PERFORMANCE OF NANO-COMPOSITE ARTIFICIAL DENTURE TEETH

Statement of Problem: Civilizing the wear resistance of artificial denture teeth is of importance to prosthodontic patients, as wear may affect the denture esthetics and functions. To counteract this problem, artificial teeth with increased wear resistance had been introduced in the market. Aim: The aim of the current study was to compare the amount of wear between nanocomposite and acrylic (PMMA) artificial teeth.Materials and methods: Ten teeth were fabricated (reproduced) from nanocomposite (Z350) by duplicating one tooth from the ready-made conventional acrylic artificial teeth. Fifteen artificial teeth were chosen from ready-made acrylic resin teeth. Mandibular 1st molars were only chosen for testing. The 2-body wear testing was performed using multi-modal ROBOTA chewing simulator. Test samples were mounted against 600 grit sandpaper and tested under a load of 700 gram for 10,000 cycles of rotation. Height and weight were measured before and after wear test for each specimen to determine the loss in both. Qualitative analysis of the wear areas was completed using USB Digital microscope with a built-in camera connected with an IBM compatible personal computer using a fixed magnification of 25X. Results: It was found that Nano-composite group recorded higher height loss mean value than conventional group height loss mean value. The difference between both groups was statistically non-significant (p>0.05) as indicated by unpaired t-test. Also Nano-composite group recorded higher weight loss mean value than conventional group weight loss mean value. The difference between both groups was statistically non-significant (p>0.05) as indicated by unpaired t-test.Conclusions: Nano-composite teeth exhibited non-significant higher wear than conventional artificial acrylic teeth.

Web Camera Based Eye Tracking to Assess Visual Memory on a Visual Paired Comparison Task.

Background: Web cameras are increasingly part of the standard hardware of most smart devices. Eye movements can often provide a noninvasive “window on the brain,” and the recording of eye movements using web cameras is a burgeoning area of research.Objective: This study investigated a novel methodology for administering a visual paired comparison (VPC) decisional task using a web camera.To further assess this method, we examined the correlation between a standard eye-tracking camera automated scoring procedure [obtaining images at 60 frames per second (FPS)] and a manually scored procedure using a built-in laptop web camera (obtaining images at 3 FPS).Methods: This was an observational study of 54 clinically normal older adults.Subjects completed three in-clinic visits with simultaneous recording of eye movements on a VPC decision task by a standard eye tracker camera and a built-in laptop-based web camera. Inter-rater reliability was analyzed using Siegel and Castellan's kappa formula. Pearson correlations were used to investigate the correlation between VPC performance using a standard eye tracker camera and a built-in web camera.Results: Strong associations were observed on VPC mean novelty preference score between the 60 FPS eye tracker and 3 FPS built-in web camera at each of the three visits (r = 0.88–0.92). Inter-rater agreement of web camera scoring at each time point was high (κ = 0.81–0.88). There were strong relationships on VPC mean novelty preference score between 10, 5, and 3 FPS training sets (r = 0.88–0.94). Significantly fewer data quality issues were encountered using the built-in web camera.Conclusions: Human scoring of a VPC decisional task using a built-in laptop web camera correlated strongly with automated scoring of the same task using a standard high frame rate eye tracker camera.While this method is not suitable for eye tracking paradigms requiring the collection and analysis of fine-grained metrics, such as fixation points, built-in web cameras are a standard feature of most smart devices (e.g., laptops, tablets, smart phones) and can be effectively employed to track eye movements on decisional tasks with high accuracy and minimal cost.

An Inventive and Innovative Alternate for Legacy Chain Pulling System through Internet of Things

<p class="Normal1">Indian Railways made a move in replacing the chain pulling system with the new mobile based communication system where the loco pilot’s mobile phone number shall be shared with all the passengers through a message. Despite the efforts taken to remove the chains from the train, there is a great probability of misuse through the mobile phone number provided. We aim to build a more efficient and secure solution based on the Internet of Things, which is a buzz word in the market. Our proposed system provides an alarm fixed at specific locations in the compartments of a train. In case of emergency, the passenger has to press the alarms’ button, which captures the scene using a built-in digital camera. The system also alarms the Loco-Pilot, Travelling Ticket Examiner, as well as the compartment so as to provide immediate possible help through the fellow co-passengers. The pilot slows down the train to an optimum speed whilst the travelling ticket examiner checks and confirms the pilot whether he has to stop the train. The entire system can be controlled through an authenticated mobile application provided to the ticket examiner. The pictures captured by the camera and other crucial details are uploaded to a cloud-based real-time database. Thus, saving time and taxpayers’ money as well as helping the railways to perform analytics and come up with feasible solutions to the problems of the passengers. The system has the potential to deal with the most prevailing cargo theft like that of coal, by alerting the staff without having to stop the train, making the convicts’ escapes impossible. This also definitely avoids the improper pulling of chains and thereby not causing any hassle to the passengers as well as diminishes the economic loss to the government by reducing the time delay.</p>

Remote autopsy services: A feasibility study on nine cases

Introduction We have conducted a feasibility study on remote autopsy services in order to increase the flexibility of the service with benefits for teaching and interdepartmental collaboration. Methods Three senior staff pathologists, one senior autopsy technician and one junior resident participated in the study. Nine autopsies were performed by the autopsy technician or resident, supervised by the primary pathologist, through the secure, double encrypted video link using Jabber Video (Cisco) with a high-speed broadband connection. The primary pathologist and autopsy room each connected to the secure virtual meeting room using 14″ laptops with in-built cameras (Hewlett-Packard). A portable high-definition web camera (Cisco) was used in the autopsy room. Primary and secondary pathologists independently interpreted and later compared gross findings for the purpose of quality assurance. The video was streamed live only during consultations and interpretation. A satisfaction survey on technical and professional aspects of the study was conducted. Results Independent interpretations of gross findings between primary and secondary pathologists yielded full agreement. A definite cause of death in one complex autopsy was determined following discussions between pathologists and reviews of the clinical notes. Our satisfaction level with the technical and professional aspects of the study was 87% and 97%, respectively. Discussion Remote autopsy services are found to be feasible in the hands of experienced staff, with increased flexibility and interest of autopsy technicians in the service as a result.

Accuracy of smartphone apps for heart rate measurement.

Background Smartphone manufacturers offer mobile health monitoring technology to their customers, including apps using the built-in camera for heart rate assessment. This study aimed to test the diagnostic accuracy of such heart rate measuring apps in clinical practice. Methods The feasibility and accuracy of measuring heart rate was tested on four commercially available apps using both iPhone 4 and iPhone 5. 'Instant Heart Rate' (IHR) and 'Heart Fitness' (HF) work with contact photoplethysmography (contact of fingertip to built-in camera), while 'Whats My Heart Rate' (WMH) and 'Cardiio Version' (CAR) work with non-contact photoplethysmography. The measurements were compared to electrocardiogram and pulse oximetry-derived heart rate. Results Heart rate measurement using app-based photoplethysmography was performed on 108 randomly selected patients. The electrocardiogram-derived heart rate correlated well with pulse oximetry ( r = 0.92), IHR ( r = 0.83) and HF ( r = 0.96), but somewhat less with WMH ( r = 0.62) and CAR ( r = 0.60). The accuracy of app-measured heart rate as compared to electrocardiogram, reported as mean absolute error (in bpm ± standard error) was 2 ± 0.35 (pulse oximetry), 4.5 ± 1.1 (IHR), 2 ± 0.5 (HF), 7.1 ± 1.4 (WMH) and 8.1 ± 1.4 (CAR). Conclusions We found substantial performance differences between the four studied heart rate measuring apps. The two contact photoplethysmography-based apps had higher feasibility and better accuracy for heart rate measurement than the two non-contact photoplethysmography-based apps.

Surveying ionizing radiations in real time using a smartphone

Surveying ionizing radiations of the surrounding with a smartphone provides a low-cost and convenient utility for the general public. We developed a smartphone application (App) that uses the built-in camera with a CMOS sensor and a radiation signal extraction algorithm. After a calibration through a series of radiation exposures, the App could display radiation dose rate and cumulative dose in real time without requiring covering the camera lens. A smartphone with this App can be used as a fast survey tool for ionizing radiations.

Resting and Postexercise Heart Rate Detection From Fingertip and Facial Photoplethysmography Using a Smartphone Camera: A Validation Study.

BackgroundModern smartphones allow measurement of heart rate (HR) by detecting pulsatile photoplethysmographic (PPG) signals with built-in cameras from the fingertips or the face, without physical contact, by extracting subtle beat-to-beat variations of skin color.ObjectiveThe objective of our study was to evaluate the accuracy of HR measurements at rest and after exercise using a smartphone-based PPG detection app.MethodsA total of 40 healthy participants (20 men; mean age 24.7, SD 5.2 years; von Luschan skin color range 14-27) underwent treadmill exercise using the Bruce protocol. We recorded simultaneous PPG signals for each participant by having them (1) facing the front camera and (2) placing their index fingertip over an iPhone’s back camera. We analyzed the PPG signals from the Cardiio-Heart Rate Monitor + 7 Minute Workout (Cardiio) smartphone app for HR measurements compared with a continuous 12-lead electrocardiogram (ECG) as the reference. Recordings of 20 seconds’ duration each were acquired at rest, and immediately after moderate- (50%-70% maximum HR) and vigorous- (70%-85% maximum HR) intensity exercise, and repeated successively until return to resting HR. We used Bland-Altman plots to examine agreement between ECG and PPG-estimated HR. The accuracy criterion was root mean square error (RMSE) ≤5 beats/min or ≤10%, whichever was greater, according to the American National Standards Institute/Association for the Advancement of Medical Instrumentation EC-13 standard.ResultsWe analyzed a total of 631 fingertip and 626 facial PPG measurements. Fingertip PPG-estimated HRs were strongly correlated with resting ECG HR (r=.997, RMSE=1.03 beats/min or 1.40%), postmoderate-intensity exercise (r=.994, RMSE=2.15 beats/min or 2.53%), and postvigorous-intensity exercise HR (r=.995, RMSE=2.01 beats/min or 1.93%). The correlation of facial PPG-estimated HR was stronger with resting ECG HR (r=.997, RMSE=1.02 beats/min or 1.44%) than with postmoderate-intensity exercise (r=.982, RMSE=3.68 beats/min or 4.11%) or with postvigorous-intensity exercise (r=.980, RMSE=3.84 beats/min or 3.73%). Bland-Altman plots showed better agreement between ECG and fingertip PPG-estimated HR than between ECG and facial PPG-estimated HR.ConclusionsWe found that HR detection by the Cardiio smartphone app was accurate at rest and after moderate- and vigorous-intensity exercise in a healthy young adult sample. Contact-free facial PPG detection is more convenient but is less accurate than finger PPG due to body motion after exercise.

Real-time heart activity monitoring with optical illusion using a smartphone

In this study, we obtained a pulsatile photoplethysmogram (PPG) signal from a fingertip using the built-in camera of an iPhone 6 s and displayed a real-time heart activity images with holographic projection on a smartphone screen. Our proposed heart activity hologram is simple and can be easily realized with only a smartphone and overhead projector (OHP) film. A square pyramid-shaped OHP film was positioned on a smartphone screen. The actual cardiac cycle on the smartphone screen was projected onto the film while measuring the pulsatile signal from a fingertip placed on the smartphone’s camera. The heart’s beat-to-beat time interval was then recorded. This approach enables observation of one’s own virtual heart activity in real time, rather than seeing a pulsatile signal graphically on a smartphone. To investigate the feasibility of this heart activity monitoring based on holographic projection, we tested it under different conditions in terms of environmental light, smartphone screen light intensity, and film color, and quantified the contrast-to-noise ratio for comparison.

보안레벨 조절이 가능한 바이오메트릭 인증 기법

지문은 사람마다 고유하며 디지털 데이터로 표현할 수 있는 생체 정보이다. 지문은 사람 몸의 일부이기 때문에, 지문인식은 패스워드나 신분증을 이용한 방법보다 사용하기 편리하다. 더불어, 최근 보급되고 있는 스마트폰은 카메라 및 지문인식 센서가 내장되어 있어서, 바이오메트릭 인증에 대한 사용자의 수요가 증가하고 있다. 하지만 지문은 쉽게 복제가 가능하고 한 번 도용되면 해당 지문을 다시 사용할 수 없는 단점이 있다. 따라서, 바이오메트릭 데이터는 원본을 변형하여 등록 및 인증해야 한다. 기존의 패스코드 입력 방식은 지문인식 센서 외에 별도의 입력 모듈이 필요하기 때문에 경제성과 사용성이 떨어진다. 본 논문에서는 사용성과 경제성을 고려한 취소 가능한 바이오메트릭 인증 기법을 제안한다. 제안한 인증 기법은 취소 가능한 바이오메트릭 템플릿 생성, 바이오메트릭 템플릿 등록 그리고 사용자 인증 프로토콜로 구성되며, 사용된 지문 개수와 스캔 타임에 따라서 보안레벨을 조절할 수 있다. 더불어, 제안한 방법이 전사적 공격과 능동적 공격으로부터 안전함을 분석하였다. A fingerprint is unique to each person and can be represented as a digital form. As the fingerprint is the part of human body, fingerprint recognition is much more easy to use and secure rather than using password or resident card for user authentication. In addition, as the newly released smart phones have built-in camera and fingerprint sensors, the demand for biometric authentication is increasing rapidly. But, the drawback is that the fingerprint can be counterfeited easily and if it's exposed to the hacker, it cannot be reused. Thus, the original fingerprint template should be transformed for registration and authentication purposes. Existing transformation functions use passcode to transform the original template to the cancelable form. Additional module is needed to input the passcode, so it requires more cost and lowers the usability. In this paper, we propose biometric authentication scheme that is economic and easy to use. The proposed scheme is consisted of cancelable biometric template creation, registration and user authentication protocols, and can control several security levels by configuring the number of fingerprints and scan times. We also analyzed that our scheme is secure against the brute-force attack and the active attacks.

Magnetic Levitation Coupled with Portable Imaging and Analysis for Disease Diagnostics.

Currently, many clinical diagnostic procedures are complex, costly, inefficient, and inaccessible to a large population in the world. The requirements for specialized equipment and trained personnel require that many diagnostic tests be performed at remote, centralized clinical laboratories. Magnetic levitation is a simple yet powerful technique and can be applied to levitate cells, which are suspended in a paramagnetic solution and placed in a magnetic field, at a position determined by equilibrium between a magnetic force and a buoyancy force. Here, we present a versatile platform technology designed for point-of-care diagnostics which uses magnetic levitation coupled to microscopic imaging and automated analysis to determine the density distribution of a patient's cells as a useful diagnostic indicator. We present two platforms operating on this principle: (i) a smartphone-compatible version of the technology, where the built-in smartphone camera is used to image cells in the magnetic field and a smartphone application processes the images and to measures the density distribution of the cells and (ii) a self-contained version where a camera board is used to capture images and an embedded processing unit with attached thin-film-transistor (TFT) screen measures and displays the results. Demonstrated applications include: (i) measuring the altered distribution of a cell population with a disease phenotype compared to a healthy phenotype, which is applied to sickle cell disease diagnosis, and (ii) separation of different cell types based on their characteristic densities, which is applied to separate white blood cells from red blood cells for white blood cell cytometry. These applications, as well as future extensions of the essential density-based measurements enabled by this portable, user-friendly platform technology, will significantly enhance disease diagnostic capabilities at the point of care.

Automated Moving Object Classification in Wireless Multimedia Sensor Networks

The use of wireless multimedia sensor networks (WMSNs) for surveillance applications has attracted the interest of many researchers. As with traditional sensor networks, it is easy to deploy and operate WMSNs. With inclusion of multimedia devices in wireless sensor networks, it is possible to provide data to users that is more meaningful than that provided by scalar sensor-based systems alone; however, producing, storing, processing, analyzing, and transmitting multimedia data in sensor networks requires consideration of additional constraints, including energy, processing power, storage capacity, and communication. Furthermore, as multimedia sensors produce much more data than scalar sensors, more manpower is required to analyze multimedia data. To overcome these constraints and challenges, this paper aimed to propose a system architecture and a set of procedures for WMSNs that facilitate automatic classification of moving objects using scalar and multimedia sensors. Methods and standards for detecting and classifying a moving object, as well as transmission of the results, are described in detail. The hardware for each sensor node includes a built-in camera, a passive infrared motion sensor, a vibration sensor, and an acoustic sensor. An application using our proposed methods was developed and embedded in the multimedia sensor node. In addition, a sink station was set up and the data produced by the sensor network was collected by this server. The classification performance of the application was tested using video recorded by the sensor node. The effect of the proposed methods on power consumption was also tested and measured. The experimental results show that the proposed approach is sufficiently lightweight to be used for real-world surveillance applications.

A crop trait information acquisition system with multitag-based identification technologies for breeding precision management

This paper aims to establish a crop trait information acquisition system by combining barcode and radio frequency-based electronic identification (RFID) and near-field communication (NFC) technology applications. The system was devised to ensure (a) correct identification of each crop material and plot, (b) quick query and positioning for information collection, (c) correct combination of crop phenotypic data and images, and (d) reliable recording of periodic crop trait data with dependable transmission to the main server. This system, with multitag-based identification technology, was developed on an Android platform using the Java language. A type of RFID/NFC tag with a high-frequency chip was applied in the core, and a quick response (QR) code was used on the surface for material identification. A smartphone with NFC function can be used as an RFID reader, and its built-in camera can be used to decode QR codes. The system was used in some seed industries’ commercial breeding and in national crop variety regional trial, with its functions including reading/writing of RFID/NFC tags, decoding QR codes, acquiring crop trait information, creating field maps, and uploading data. This system provided a low-cost and highly efficient solution for crop trait information collection.

A survey of design and implementation for optical camera communication

Visible Light Communication (VLC) has emerged as a promising technology for wireless communication owing to advantages such as bandwidth, license, coexistence and security. Additionally, it was officially standardized by IEEE 802.15.7 in 2011. However, it faces certain challenges that can be considered as grounds to develop a revised version. Optical camera communication (OCC) operates in the same channel band as VLC with more advantages on receiver characteristic and is a candidate for the standardization of issues in IEEE 802.15.7r1. Specifically, OCC presents a new and inexpensive technology that is different from other technologies such as radio frequency technology. Its advantages include the usage of built-in cameras in smart devices that can act as receivers for OCC. Existing lighting systems, such as light-emitting diodes (LEDs), liquid-crystal displays (LCDs), and digital signage, can operate as transmitters. This study provides an overview of extant research on the design and implementation of OCC. The analyses and discussions in the survey present relevant fields of implementation and future directions for OCC technology.