Kajian dan Implementasi Real Time Operating System pada Single Board Computer Berbasis Arm

The introduction of autonomous vehicles has the potential to reduce the number of accidents and save countless lives. These benefits can only be realized if autonomous vehicles can prove to be safer than human drivers. There is a large amount of active research around developing robust algorithms for all parts of the autonomous vehicle stack including sensing, localization, mapping, perception, prediction, planning, and control. Additionally, some of these research projects have involved the use of the Robot Operating System (ROS). However, another key aspect of realizing an autonomous vehicle is a fault-tolerant design that can ensure the safe operation of the vehicle under unfavorable conditions. The goal of this thesis is to evaluate the feasibility of adding a dedicated fault tolerance module into a ROS based architecture. The fault tolerance module is used to implement a safety controller that can take over safety-critical operations of the system when a fault is detected in the main computer. A Xilinx Zynq-7000 SoC with a dual-core ARM Cortex-A9 and an FPGA programmable logic region is chosen as the platform. The platform works in the Asymmetric Multiprocessing (AMP) configuration with a Linux based operating system on one core and a real-time operating system (RTOS) on the other. Results are gathered from an implementation done on a ROS based mobile robot platform.

Smart surveillance systems are used to monitor specific areas, such as homes, buildings, and borders, and these systems can effectively detect any threats. In this work, we investigate the design of low-cost multiunit surveillance systems that can control numerous surveillance cameras to track multiple objects (i.e., people, cars, and guns) and promptly detect human activity in real time using low computational systems, such as compact or single board computers. Deep learning techniques are employed to detect certain objects to surveil homes/buildings and recognize suspicious and vital events to ensure that the system can alarm officers of relevant events, such as stranger intrusions, the presence of guns, suspicious movements, and identified fugitives. The proposed model is tested on two computational systems, specifically, a single board computer (Raspberry Pi) with the Raspbian OS and a compact computer (Intel NUC) with the Windows OS. In both systems, we employ components, such as a camera to stream real-time video and an ultrasonic sensor to alarm personnel of threats when movement is detected in restricted areas or near walls. The system program is coded in Python, and a convolutional neural network (CNN) is used to perform recognition. The program is optimized by using a foreground object detection algorithm to improve recognition in terms of both accuracy and speed. The saliency algorithm is used to slice certain required objects from scenes, such as humans, cars, and airplanes. In this regard, two saliency algorithms, based on local and global patch saliency detection are considered. We develop a system that combines two saliency approaches and recognizes the features extracted using these saliency techniques with a conventional neural network. The field results demonstrate a significant improvement in detection, ranging between 34% and 99.9% for different situations. The low percentage is related to the presence of unclear objects or activities that are different from those involving humans. However, even in the case of low accuracy, recognition and threat identification are performed with an accuracy of 100% in approximately 0.7 s, even when using computer systems with relatively weak hardware specifications, such as a single board computer (Raspberry Pi). These results prove that the proposed system can be practically used to design a low-cost and intelligent security and tracking system.

This paper presents design and implementation of a dual-band RF system-in-package (SiP) module for radar application. Four channel RF transceivers, each of which consists of dual-band RF front-end, ADC and DAC, are integrated in this SiP module. S and P band RF front-end of the transceiver employ common Intermediate Frequency (IF) window to share digitization circuits efficiently. To achieve more miniaturized package level of SiP, Package-on-Package technology is adopted and realized by stacking two multi-layer organic substrates vertically, which interconnected by Through Mold Via (TMV) and BGA. Dual-band RF front-end is mounted on the top RO4350B substrate, and four-channel ADC and DAC are molding on the bottom BT substrate. With the integration of 50 chips and 251 passive components, this SiP module retains small form factor and measures $\pmb{3.8\times 4\times 0.4}\mathbf{cm}^{\pmb{3}}$ . The simulation results show that the insertion loss of RF transmission paths are better than 0.4 dB with 60 dB channel isolation, the crosstalk between analog and digital paths is less than -60 dB, and each chip junction temperature is below 100°C in the condition of full load. The above evaluation indicates that the proposed RF SiP module can achieve the optimization of electrical performance, reliability and miniaturization simultaneously.

NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Using Programming Projects in an Operating Systems Course as a Capstone Software Engineering Experience Computer Engineering Technology students at the University of Dayton take two fundamental programming courses teaching the basics of algorithmic problem solving along with the VBA and C++ syntaxes. These courses develop a strong programming foundation for the students; however, they lack the ability to introduce software programming within larger software systems. The final course related to software development is a required operating systems course. This course contains three fundamental goals: to develop the students’ understanding of key operating system concepts, to increase the students’ software engineering capabilities, and to introduce the students to the internal workings of the Linux and Windows operating systems. The operating systems course relies heavily on software programming exercises as a key instrument in teaching students the framework and applications of modern operating systems. The unique aspect of this approach is that the programming projects are designed not as standalone activities, but instead as individual components of a larger software system. Therefore, each programming project focuses not just on learning new syntax related to operating system concepts, but also in how these concepts are relevant to the software system being developed. Students develop programs for both the Microsoft Windows and Linux operating systems, working heavily with their associated application programming interfaces and investigating processes, threads, synchronization, input and output, and scheduling issues. A complete course overview and synopsis of the software programming projects will be presented along with student performance and comments from an end of the semester survey. Introduction The Computer Engineering Technology (CET) Program at the University of Dayton (UD) was started in 1999 and included two software programming courses. These courses predominately focused on teaching the fundamentals of software programming and the syntax associated with the VBA and C++ languages. Likewise, to satisfy the ABET outcome requirements for computer engineering technology programs, the ETC Program at UD also required a new 3 credit lecture course entitled “Concepts & Applications of Operating Systems” to be taken during the students’ Junior year of study.1 This course was structured to provide students hands-on exposure to the internal workings of modern operating systems. During the 2004/2005 academic year, the material being taught in the software programming was evaluated. In accordance with the Computing Curricula 2001 (CC2001) report by the Computer Society of the Institute for Electrical and Electronic Engineers (IEEE-CS) and the Association for Computing Machinery (ACM), the two software programming courses being taught fell within the traditional imperative-first approach. This approach starts students off with software programming activities without any real preparations.2 After careful review, it was found that the student population being served needed to be taught the algorithmic thought process prior to the syntax as many of the students had no prior exposure to software programming and were struggling more with defining the problem solutions than with the specific syntax being taught.3 A modified algorithms-first approach from CC2001 report was applied to these courses. Instead

This paper discuss on how to develop a hard real-time machine control system with Microsoft Windows NT Operating System, where the respond must be within 0.5 milliseconds. The attempt to use a general-purpose operating system (Microsoft Windows NT 4.0 Workstation) is because there is abundance of Commercial-Off-the-Shelf Components (COTS), easily available tools (compilers, and 3 party tools) and need not to learn another operating system behavior. The most important factor is there is no single dominant operating system or tools vendor for real-time operating system. Since the no single dominant real-time operating system development under real-time operating system is riskier and more costly. Ideally codes must be portable between different operating system where it is apparent with Windows platforms, Windows 95/98, Windows ME, Windows 2000, Windows XP or even Windows CE. Firstly study was done on how Microsoft Windows NT operating system works internally from materials from Microsoft Software Development Network (MSDN). Secondly study was done how to take advantage of the operating system to create a real time application. Microsoft Windows NT is a general purpose operating system that does not support real time application development, but it has all the vital elements that a real time operating system needs. The vital elements are priority-driven, preemptive scheduler, preemptive interrupt handler (for critical interrupts), deferred procedure calls (DPC) for non-critical (DPC executes after ISR), synchronization and deterministic response time. With these vital elements and some modification to application codes to enable it to execute in higher priority level, would result a real time application. This does not mean changing all the codes to higher priority is the solution, as it would cause system to malfunction as other device driver or low-level interface run at high priority too and this would lock up the system. With the combination of priority level, synchronization a complete real time solution can be implemented and this paper covers the concept. This concept also explains what was done to overcome the need of special hardware (as recommended) to accomplish hard real-time application with the response of 0.5 milliseconds.

There many applications throughout industry and government requiring real-time computing. Any application that monitors and/or controls a process would fit into this category. Some examples are: Nuclear power plants, Steel mills, Space program, etc. General Atomics uses eight real-time computer systems for control and high speed data acquisition required to run the nuclear fusion experiments. Real-Time computing can be defined as the ability to respond to asynchronous external events in a predictable (preferably fast) time frame. Real-Time computer systems are similar to other computers in many ways and may by used for general computing requirements such as Time-Sharing. However special hardware, operating systems and software had to be developed to meet the requirement for real-time computing. Traditionally, real-time computing has been a realm of proprietary operating systems with real-time applications written in FORTRAN and assembly language. In the past, these systems adequately served the needs of the real-time world. Many of these systems that were developed 15 years ago are still being used today. However the real-time world is now changing, demanding new systems to be developed. This paper gives a description of general real-time computer systems and how they differ from other systems. However, the main purpose of this paper is to give a detailed technical description of the hardware and operating systems of an existing proprietary system and a real-time UNIX system. The two real-time computer systems described in detail are Modcomp Classic III/95 with the MAX IV operating system and Modcomp TRI-D 9750 with the REAL/IX.2 operating system.

In order to achieve fast and efficient data acquisition and digital-to-analog conversion based on ARM9 Microcontroller S3C2410 and embedded real-time operating system μC/OS-II of multi-tasking A / D acquisition system. Not only able to finish with high precision, reliable, stable, real-time multi-channel analog signals and on-off signal data acquisition, and displays it on the LCD in real time. Completed in ADS1.2 compiled environment, system software using C language and assembly language mix programming, which makes full use of the advantages of different languages. This paper constructs the system's overall design, hardware circuit design method is given in detail, at the same time describes key transplant μ C/OS-II embedded operating systems and software design. Keywordsata Acquisition; LCD;Real-time Display

Traditional forensic analysis of hard disks and external media typically involves a powered down machine and “dead analysis” of these devices. Forensic acquisition of hard drives and external media has traditionally been by one of several means: standalone forensic duplicator; using a hardware write-blocker or dock attached to a laptop, computer, workstation, etc., forensic operating systems that live boot from a USB, CD/DVD or virtual machines with preinstalled operating systems. Standalone forensics acquisition and imaging devices generally cost thousands of dollars. In this paper, we propose the use of single board computers as forensic imaging devices. Single board computers can provide a low budget forensic imaging solution that can be used in a lab, remote acquisition, or even be configured as portable imaging devices. This project tests different ARM processor based single board computers and the software available at the present time. The project includes image acquisition using a write-blocker, software write-blockers and without write-blockers to test the various configurations. The final results demonstrate clearly that ARM based single board computers can be used as low cost and low energy forensic imaging devices.

Operating system is a compulsory subject students STMIK Indonesia Padang. This course describes computer's operating system for control and management of hardware and computer software. Computer operating system is located on the first layer of hard disk drive. When computer is turned on, software first work is operating system and other new applications are processed. The results of observations on STMIK Indonesia Padang, 30% of students have not been able to understand the subject of Operating System. Instructional media should be formulated so that material is easy to understand. The computer as a learning tool Operating System can be made interactive learning media applications. Many interactive CD Operating System in circulation, only contains general material and do not develop subject of discussion. Research objective of designing learning media Operating System using Macromedia Flash, which can be used as ingredients in learning process for students. The subjects were students STMIK Indonesia Padang subjects Operating Systems.

Information Technology has evolved over a period of time from Electronic Data Processors (EDP) to Cloud based technologies. Software is a critical component in this industry. The core product component in software is the set of instructions in the form of source code. During inception of the industry, source code was accessible at no cost. In the next era of information technology (1970's & 1980's), programs which were earlier available free of cost were sold at a price through licensing. During mid and early 1980's open source and hardware integrated software emerged. Similar trend was visible in system software market, especially in the operating system software market. Over a period of time Microsoft operating system emerged as one of the dominant players in the market. However, in the recent past Microsoft has considerably lost its market share in operating system products from 94.38% in June 2007 to 84% in May 2014. This paper captures the trend in operating system software market and analyses customers' preference to switch over from the current operating system. The trend in the market was analyzed through secondary data on market share and the customer preference to switch over was captured through a survey of engineers at various multinational IT firms in Bangalore. The study identified that the current trend could be moving towards open source or hardware integrated operating system from proprietary operating software. The survey identified that higher percentage of users preferred to switch over from the current operating system on desktops, laptops and workstations to either open source or hardware integrated operating system except servers.

An important goal of software security is to ensure sensitive/secret data owned by a program shall be exclusively accessible by the program. An obstacle to such security goal is that modern commodity operating systems (OS) for the sake of speed and flexibility have a unified linear address space--any OS kernel program can access all the linear addresses. As a result, rootkits or malicious system software are able to control the OS virtual address space, harvest the sensitive data used by software programs on the compromised computer, and report the data to remote entities controlled by hackers.In this paper, we present a holistic approach against sophisticated malware. Instead of focusing on the security of various abstraction layers of OS, we utilize the hardware techniques to directly provide the trust services to software programs. Without modifying OS, we leverage the virtual machine monitor technologies to create a lightweight hypervisor for fine-grain software runtime memory protection. As a result, a program's memory could be hidden from other high privilege system software in a single commodity OS. In addition, we propose the data locker component in the hypervisor, which prevents the sensitive data of software program in persistent storage from leaking to rootkits or other malware. For the performance evaluation, the implementation based on hardware-assisted x86 virtualization technology is presented and experimental results are reported.

Interconnected devices are becoming attractive solutions to integrate physical parameters and making them more accessible for further analysis. Edge devices, located at the end of the physical world, measure and transfer data to the remote server using either wired or wireless communication. The exploding number of sensors, being used in the Internet of Things (IoT), medical fields, or industry, are demanding huge bandwidth and computational capabilities in the cloud, to be processed by Artificial Neural Networks (ANNs) – especially, processing audio, video and images from hundreds of edge devices. Additionally, continuous transmission of information to the remote server not only hampers privacy but also increases latency and takes more power. Deep Neural Network (DNN) is proving to be very effective for cognitive tasks, such as speech recognition, object detection, etc., and attracting researchers to apply it in edge devices. Microcontrollers and single-board computers are the most commonly used types of edge devices. These have gone through significant advancements over the years and capable of performing more sophisticated computations, making it a reasonable choice to implement DNN. In this thesis, a DNN model is trained and implemented for Keyword Spotting (KWS) on two types of edge devices: a bare-metal embedded device (microcontroller) and a robot car. The unnecessary components and noise of audio samples are removed, and speech features are extracted using Mel-Frequency Cepstral Co-efficient (MFCC). In the bare-metal microcontroller platform, these features are efficiently extracted using Digital Signal Processing (DSP) library, which makes the calculation much faster. A Depth wise Separable Convolutional Neural Network (DSCNN) based model is proposed and trained with an accuracy of about 91% with only 721 thousand trainable parameters. After implementing the DNN on the microcontroller, the converted model takes only 11.52 Kbyte (2.16%) RAM and 169.63 Kbyte (8.48%) Flash of the test device. It needs to perform 287,673 Multiply-and-Accumulate (MACC) operations and takes about 7ms to execute the model. This trained model is also implemented on the robot car, Jetbot, and designed a voice-controlled robotic vehicle. This robot accepts few selected voice commands-such as “go”, “stop”, etc. and executes accordingly with reasonable accuracy. The Jetbot takes about 15ms to execute the KWS. Thus, this study demonstrates the implementation of Neural Network based KWS on two different types of edge devices: a bare-metal embedded device without any Operating System (OS) and a robot car running on embedded Linux OS. It also shows the feasibility of bare-metal offline KWS implementation for autonomous systems, particularly autonomous vehicles.

The design and development of image processing units (IPUs) has traditionally involved trade-offs between cost, real-time properties, portability, and ease of programming. A standard PC can be turned into an IPU relatively easily with the help of readily available computer vision libraries, but the end result will not be portable, and may be costly. Similarly, one can use field programmable gate arrays (FPGAs) as the base for an IPU, but they are expensive and require hardware-level programming. Finally, general purpose embedded hardware tends to be under-powered and difficult to develop for due to poor support for running advanced software. In recent years a new option has surfaced: single-board computers (SBCs). These generally inexpensive embedded devices would be attractive as a platform on which to develop IPUs due to their inherent portability and good compatibility with existing computer vision (CV) software. However, whether their performance is sufficient for real-time image processing has thus far remained an open question. Most SBCs (especially the ultra-low-cost ones which we target) do not offer CUDA/OpenCL support which makes it difficult to port GPU-based CV applications. In order to utilize the full power of the SBCs, their GPUs need to be used. In our attempts at doing this, we have observed that the CV algorithms which an IPU uses have to be re-designed according to the OpenGL support available on these devices. This work presents a framework where a selection of CV algorithms have been designed in a way that they optimize performance on SBCs while still maintaining portability across devices which offer OpenGL ES 2.0 support. Furthermore, this paper demonstrates an IPU based on a representative SBC (namely the Raspberry Pi) along with two CV applications backed by it. The robustness of the applications as well as the performance of the IPU are evaluated to show that SPCs can be used to build IPUs capable of producing accurate data in real time. This opens the possibilities of large scale economically deployment of vision system especially in remote and barren lands. Finally, the software developed as a part of this work has been released open source.

Conceptual design of autonomous emergency operation system for nuclear power plants and its prototype

Optimizing security and quality of service in a real-time operating system using multi-objective Bat algorithm