Raspberry Pi based automatic temperature measurement and logging system for solar thermal purposes

For automatic temperature measuring and logging purposes in solar thermal experiments, a single board computer - Raspberry Pi based and sensor system is proposed. Different data sets are observed for sensors, thermometers, and thermocouples and they are compared. The consistency of the automated temperature measurement system is also verified.

Means and Methods of Efficiency Estimation of Video Stream Transmission Based on GigE Vision Technology Using Application Processor

The paper investigates the possibility of efficient implementation of a GigE Vision compatible video stream source on a computing platform based on a system-on-a-chip with general-purpose ARM processor cores. In particular, to implement the aforementioned video source, a proprietary prototype of a GigE Vision compatible camera was developed based on the Raspberry Pi 4 single-board computer. This computing platform was chosen due to its widespread use and wide community support. The software part of the camera is implemented using the Video4Linux and Aravis libraries. The first library is used for the primary image capturing from a video sensor connected to a single board computer. The second library is intended for forming and transmission of video stream frames compatible with GigE Vision technology over the network. To estimate the delays in the transmission of a video stream over an Ethernet channel, a methodology based on the Precise Time Protocol (PTP) has been proposed and applied. During the experiments, it was found that the software implementation of a GigE Vision compatible camera on single-board computers with general-purpose processor cores is quite promising. Without additional optimization, such an implementation can be successfully used to transmit small frames (with a resolution of up to 640 × 480 pixels), giving a delay less than 10 ms. At the same time, some additional optimizations may be required to transmit larger frames. Namely, a MTU (maximum transmission unit) size value plays the crucial role in latency formation. Thus, to implement a faster camera, it is necessary to select a platform that supports the largest possible MTU (unfortunately, it turned out that it is not possible with Raspberry Pi 4, as it supports relatively small MTU size of up to 2000 bytes). In addition, the image format conversion procedure can noticeably affect the delay. Therefore, it is highly desirable to avoid any frame processing on the transmitter side and, if it is possible, to broadcast raw images. If the conversion of the frame format is necessary, the platform should be chosen so that there are free computing cores on it, which will permit to distribute all necessary frame conversions between these cores using parallelization techniques.

Ubiquitous Control of a CNC Machine: Proof of Concept for Industrial IoT Applications

In this paper, an integrated system to control and manage a state-of-the-art industrial computer numerical control (CNC) machine (Studer S33) using a commercially available tablet (Samsung Galaxy Tablet S2) is presented as a proof of concept (PoC) for the ubiquitous control of industrial machines. As a PoC, the proposed system provides useful insights to support the further development of full-fledged systems for Industrial Internet of Things (IIoT) applications. The proposed system allows for the quasi-decentralisation of the control architecture of conventional programmable logic controller (PLC)-based industrial control systems (ICSs) through data and information exchange over the transmission control protocol and the internet protocol (TCP/IP) suite using multiple agents. Based on the TCP/IP suite, a network device (Samsung Galaxy Tablet S2) and a process field net (PROFINET) device (Siemens Simatic S7-1200) are interfaced using a single-board computer (Raspberry Pi 4). An override system mainly comprising emergency stop and acknowledge buttons is also configured using the single-board computer. The input signals from the override system are transmitted to the PROFINET device (i.e., the industrial control unit (ICU)) over TCP/IP. A fully functional working prototype is realised as a PoC for an integrated system designated for the wireless and ubiquitous control of the CNC machine. The working prototype as an entity mainly comprises a mobile (handheld) touch-sensitive human-machine interface (HMI), a shielded single-board computer, and an override system, all fitted into a compact case with physical dimensions of 300 mm by 180 mm by 175 mm. To avert potential cyber attacks or threats to a reasonable extent and to guarantee the security of the PoC, a multi-factor authentication (MFA) including an administrative password and an IP address is implemented to control the access to the web-based ubiquitous HMI proffered by the PoC.

PROTOTYPE DETEKSI OBJEK MENGGUNAKAN RASPBERRY PI MELALUI MODUL SENSOR ULTRASONIK HC-SR04

Pendekatan deteksi objek yang dilakukan oleh radar pada perkapalan sangat intuitif dan sensitif terhadap benda yang berada dalam wilayah terjangkau sensor aktif. Menjadi suatu hal yang sangat bermanfaat, crew kapal memantau 24 Jam / 7 hari perjalanan menuju destinasi dermaga berikutnya. Sensor deteksi sangat peka terhadap wilayah yang terjangkau akan memberikan peringatan berupa sirene jika didepan terdapat halang rintang. Untuk segera menghindari atau memperlambat perjalanan kapal. Penulis membuat peneliti sebagai simulasi implementasi deteksi kapal dibuat menggunakan raspberry sebagai single board computer atau papan tunggal komputer sebagai otak sistem bekerja. Prototype ini menggunakan sensor ultrasonik HC-SR04 yang digerakan dengan 1 motor servo, dipilih sensor ultrasonic HC-SR04 tersebut karena memiliki spesifikasi yang memadai. Hasil dari pengukuran objek ditampilkan dengan aplikasi pemograman python. Dari hasil pengujian alat yaitu mampu mendeteksi objek antara 5 cm dari depan radar dan jarak maksimum 30 cm dan diperoleh tingkat kesalahan pengukuran jarak dan ketinggian sebesar 1 – 3 cm sedangkan untuk sudut 2o s/d 5o.

Raspberry Pi-based mobile system of the pupil size evaluation

The article considers development of a human pupil measuring system on the Raspberry platform. The system is aimed at evaluating the variations of the human pupil diameter or area in the process of watching test images or video recordings. To reduce the interference from the eye surface the camera uses a band-stop color glass filter PS 13. In order to increase the pupil image contrast, IR LED backlighting of the eye is implemented. To provide the mobility of the system, battery power of the single-board computer was used while the registered image and the measurement results were transmitted via a Wi-Fi channel. The video camera and the single-board computer Raspberry Pi 4 with the battery bay are attached to the head-mounted flexible belt. The article gives the operation duration evaluation of the battery-supplied system. During the first stage of image processing, binarization by the threshold was performed. The threshold is determined by the image brightness histogram. Since the study is focused on relative variations of the pupil size, the pupil diameter or area values in pixels were chosen as informative parameters. The image recording and processing frequency in the system equalled 25 Hz that provides accurate recording of the pupil variations.

Evaluación y comparación de algoritmos para la detección automática de eventos sísmicos

La detección temprana de eventos sísmicos permite reducir daños materiales, el número de personas afectadas e incluso salvar vidas. En particular, la actividad sísmica en Ecuador es alta, dado que se encuentra en el denominado Cinturón de Fuego del Pacífico. En tal contexto, el presente artículo tiene como objetivo comparar algoritmos para la detección automática de eventos sísmicos. Dicha comparación se realiza con respecto a la funcionalidad y configuración de los parámetros requeridos para cada algoritmo. Además, la implementación se lleva a cabo sobre una plataforma computacional tipo SBC (Single Board Computer) con la finalidad de obtener una herramienta portable, escalable, económica y de bajo costo computacional. Los métodos comparados son: Classic STA/LTA, Recursive STA/LTA, Delayed STA/LTA, Z-detector, Baer and Kradolfer picker y AR-AIC (Autoregressive-Akaike-Information-Criterion-picker). Para la evaluación y comparación se desarrollan múltiples experimentos empleando registros sísmicos reales proporcionados por la Red Sísmica del Austro (RSA), disponibles como fuente de entrada a los algoritmos. Como resultado se obtiene que el algoritmo Classic STA/LTA presenta el mejor rendimiento, ya que del total de eventos reales (58), solo un evento no fue detectado. Además, se consiguen 6 falsos negativos, logrando un 98,2% de precisión. Cabe recalcar que el software utilizado para la comparación de algoritmos de detección de eventos sísmicos está disponible de forma libre.