scholarly journals Open-Source Wireless Cloud-Connected Agricultural Sensor Network

2018 ◽  
Vol 7 (4) ◽  
pp. 47 ◽  
Author(s):  
Daniel Fisher ◽  
Lisa Woodruff ◽  
Saseendran Anapalli ◽  
Srinavasa Pinnamaneni
Keyword(s):  
Open Source ◽  
Data Transfer ◽  
Agricultural Research ◽  
Water System ◽  
Data Access ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Network Access ◽  
Electronic Circuitry ◽  
To Receive

Agricultural research involves study of the complex soil–plant–atmosphere–water system, and data relating to this system must be collected under often-harsh outdoor conditions in agricultural environments. Rapid advancements in electronic technologies in the last few decades, as well as more recent widespread proliferation and adoption of electronic sensing and communications, have created many options to address the needs of professional, as well as amateur, researchers. In this study, an agricultural research project was undertaken to collect data and examine the effects of different agronomic practices on yield, with the objectives being to develop a monitoring system to measure soil moisture and temperature conditions in field plots and to upload the data to an internet website. The developed system included sensor nodes consisting of sensors and electronic circuitry to read and transmit sensor data via radio and a cellular gateway to receive node data and forward the data to an internet website via cellular infrastructure. Microcontroller programs were written to control the nodes and gateway, and an internet website was configured to receive and display sensor data. The battery-powered sensor nodes cost $170 each, including electronic circuitry and sensors, and they were operated throughout the cropping season with little maintenance on a single set of batteries. The solar-powered gateway cost $163 to fabricate, plus an additional cost of $2 per month for cellular network access. Wireless and cellular data transmissions were reliable, successfully transferring 95% of sensor data to the internet website. Application of open-source hardware, wireless data transfer, and internet-based data access therefore offers many options and advantages for agricultural sensing and monitoring efforts.

scholarly journals Pengembangan Sistem Streaming Sensor Data Temperatur dan Kelembapan di Ruang Laboratorium BBTA3 Melalui Teknologi Open Source

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Arizal Akbar Zikri
Keyword(s):  
Open Source ◽  
Streaming Data ◽  
Sensor Data ◽  
Raspberry Pi ◽  
Data Streaming ◽  
Application Development ◽  
Web Browser ◽  
Streaming Application ◽  
To Receive ◽  
Data Reading

AbstractDevelopment of temperature and humidity data streaming Application from sensors in the server room is necessary to enable the operator to monitor the real-time air condition in the server room, without having to enter the room. This application development utilizes open source technology to make developers more independent and able to interact easily within the community without license hassle.Sensor data reading is done by Raspberry Pi, assigned as a producer in sending data to Kafka Cluster. Kafka is an open source technology used as tools for streaming data distributedly. One node in a cluster is set to receive sensor data, known as consumer, executes python service to handle requests from users through Server Sent Event (SSE) in form of REST API.This application is called TempHum and can be executed on Desktop (Windows, Linux, Mac OS), web browser, and smartphone (Android and iOS). Hence, the application can serve many clients in monitoring air condition in realtime.Keywords: open source, cluster, raspberry pi, kafka, python.AbstraksAplikasi streaming data sensor berupa temperatur dan kelembapan di ruang server perlu dikembangkan, sehingga memudahkan bagi operator untuk memantau kondisi udara terkini secara dinamis di ruang server tanpa harus masuk kedalam ruang tersebut. Pengembangan aplikasi dilakukan menggunakan teknologi open source agar memudahkan pengembang untuk mandiri dan berinteraksi dalam komunitas tanpa terikat dengan permasalahan lisensi.Pembacaan data sensor dilakukan oleh Raspberry Pi dan dijadikan sebagai producer untuk mengirimkan data tersebut ke Kafka Cluster. Kafka merupakan teknologi open source yang digunakan sebagai alat untuk streaming data terdistribusi. Satu node dalam cluster digunakan untuk menerima kiriman data atau dikenal sebagai consumer sekaligus menjalankan python servis untuk menangani permintaan dari pengguna aplikasi melalui Server Sent Event (SSE) dalam bentuk REST API.Aplikasi ini diberi nama TempHum dan dapat dijalankan di Desktop (Windows, Linux, Mac OS), web browser, dan smartphone (Android dan iOS), sehingga aplikasi ini dapat melayani banyak pengguna dalam memantau kondisi ruang server secara dinamis.Kata Kunci : open source, cluster, raspberry pi, kafka, python. 

Towards a scalable, open-standards service for brokering cross-protocol data transfers across multiple sources and sinks

2010 ◽  
Vol 368 (1926) ◽  
pp. 4115-4131
Author(s):  
David Meredith ◽  
Stephen Crouch ◽  
Gerson Galang ◽  
Ming Jiang ◽  
Hung Nguyen ◽  
...  
Keyword(s):  
Open Source ◽  
Design Patterns ◽  
Data Transfer ◽  
Fault Tolerant ◽  
Data Access ◽  
Third Party ◽  
Multiple Sources ◽  
Wide Range ◽  
Bulk Data ◽  
Open Standards

Data Transfer Service (DTS) is an open-source project that is developing a document-centric message model for describing a bulk data transfer activity, with an accompanying set of loosely coupled and platform-independent components for brokering the transfer of data between a wide range of (potentially incompatible) storage resources as scheduled, fault-tolerant batch jobs. The architecture scales from small embedded deployments on a single computer to large distributed deployments through an expandable ‘worker-node pool’ controlled through message-orientated middleware. Data access and transfer efficiency are maximized through the strategic placement of worker nodes at or between particular data sources/sinks. The design is inherently asynchronous, and, when third-party transfer is not available, it side-steps the bandwidth, concurrency and scalability limitations associated with buffering bytes directly through intermediary client applications. It aims to address geographical–topological deployment concerns by allowing service hosting to be either centralized (as part of a shared service) or confined to a single institution or domain. Established design patterns and open-source components are coupled with a proposal for a document-centric and open-standards-based messaging protocol. As part of the development of the message protocol, a bulk data copy activity document is proposed for the first time.

scholarly journals Implementation of a Six-Layer Smart Factory Architecture with Special Focus on Transdisciplinary Engineering Education

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2944
Author(s):  
Benjamin James Ralph ◽  
Marcel Sorger ◽  
Benjamin Schödinger ◽  
Hans-Jörg Schmölzer ◽  
Karin Hartl ◽  
...  
Keyword(s):  
Open Source ◽  
User Interfaces ◽  
Industrial Revolution ◽  
Low Cost ◽  
Material Behavior ◽  
Sensor Data ◽  
Management Tool ◽  
Special Focus ◽  
Programming Environments ◽  
Metal Processing

Smart factories are an integral element of the manufacturing infrastructure in the context of the fourth industrial revolution. Nevertheless, there is frequently a deficiency of adequate training facilities for future engineering experts in the academic environment. For this reason, this paper describes the development and implementation of two different layer architectures for the metal processing environment. The first architecture is based on low-cost but resilient devices, allowing interested parties to work with mostly open-source interfaces and standard back-end programming environments. Additionally, one proprietary and two open-source graphical user interfaces (GUIs) were developed. Those interfaces can be adapted front-end as well as back-end, ensuring a holistic comprehension of their capabilities and limits. As a result, a six-layer architecture, from digitization to an interactive project management tool, was designed and implemented in the practical workflow at the academic institution. To take the complexity of thermo-mechanical processing in the metal processing field into account, an alternative layer, connected with the thermo-mechanical treatment simulator Gleeble 3800, was designed. This framework is capable of transferring sensor data with high frequency, enabling data collection for the numerical simulation of complex material behavior under high temperature processing. Finally, the possibility of connecting both systems by using open-source software packages is demonstrated.

Concurrent and sustainable development of a local-scale digital heritage inventory through action research at Bat, Oman

2016 ◽  
Vol 6 (2) ◽  
pp. 195-212
Author(s):  
Yasuhisa Kondo ◽  
Takehiro Miki ◽  
Taichi Kuronuma ◽  
Yuichi S. Hayakawa ◽  
Kyoko Kataoka ◽  
...  
Keyword(s):  
Action Research ◽  
Open Source ◽  
Geographical Information Systems ◽  
Design Methodology ◽  
Heritage Management ◽  
Geographical Information ◽  
Network Access ◽  
Content Type ◽  
Digital Heritage ◽  
Local Agent

Purpose – The purpose of this paper is to present a concurrent implementation of sustainable inventory for the UNESCO World Heritage sites of Bat, Al-Khutm and Al-Ayn in the interior of Oman. Design/methodology/approach – A digital heritage inventory (DHI) was developed through an action research to realize demands of the local agent and to co-design the solution. The Ministry of Heritage and Culture of Oman, the local agent, demanded to have archaeological information of the sites shared with foreign expeditions, which had worked at the sites for decades, for efficient heritage management, scientific research, outreach, and education. To this end, the Bat Digital Heritage Inventory (BatDHI) was implemented by a combination of network-access-ready database application, open source geographical information systems, and a web-based map service to incorporate and visualize previous works, which were concurrently cross-checked and updated by ground-truth surveys. Findings – The online inventory made it possible to update information during archaeological fieldwork in real time and accelerated the decision-making process in heritage management by prompt data updates and visualization. Research limitations/implications – The DHI is extendable for other sites or regions. It should also be considered to install Arches, an open-source suite of digital heritage inventories. Practical implications – The BatDHI was implemented through the action research mentioned in the design/methodology/approach section and yielded the implications mentioned in the findings section. Originality/value – This paper is a challenging application of transdisciplinary approach to the sustainable heritage management, in which researchers and societal stakeholders collaborate for co-design of research agendas, co-production of knowledge, and co-dissemination of outcomes.

Industry 4.0 Digital Technologies for data collection and control

2021 ◽  
pp. 43-58
Author(s):  
S. S. Yudachev ◽  
P. A. Monakhov ◽  
N. A. Gordienko
Keyword(s):  
Data Collection ◽  
Open Source ◽  
Software Defined Radio ◽  
Block Diagram ◽  
Data Access ◽  
Gnu Radio ◽  
Time Data ◽  
Object A ◽  
Data Propagation ◽  
And Control

This article describes an attempt to create open source LabVIEW software, equivalent to data collection and control software. The proposed solution uses GNU Radio, OpenCV, Scilab, Xcos, and Comedi in Linux. GNU Radio provides a user-friendly graphical interface. Also, GNU Radio is a software-defined radio that conducts experiments in practice using software rather than the usual hardware implementation. Blocks for data propagation, code deletion with and without code tracking are created using the zero correlation zone code (ZCZ, a combination of ternary codes equal to 1, 0, and –1, which is specified in the program). Unlike MATLAB Simulink, GNU Radio is open source, i. e. free, and the concepts can be easily accessed by ordinary people without much programming experience using pre-written blocks. Calculations can be performed using OpenCV or Scilab and Xcos. Xcos is an application that is part of the Scilab mathematical modeling system, and it provides developers with the ability to design systems in the field of mechanics, hydraulics and electronics, as well as queuing systems. Xcos is a graphical interactive environment based on block modeling. The application is designed to solve problems of dynamic and situational modeling of systems, processes, devices, as well as testing and analyzing these systems. In this case, the modeled object (a system, device or process) is represented graphically by its functional parametric block diagram, which includes blocks of system elements and connections between them. The device drivers listed in Comedi are used for real-time data access. We also present an improved PyGTK-based graphical user interface for GNU Radio. English version of the article is available at URL: https://panor.ru/articles/industry-40-digital-technology-for-data-collection-and-management/65216.html

A Blockchain-Enabled Approach for Online Stream Sensor Data Protection in Cyber-Physical Manufacturing Systems

2021 ◽  
Author(s):  
Zhangyue Shi ◽  
Chenang Liu ◽  
Chen Kan ◽  
Wenmeng Tian ◽  
Yang Chen
Keyword(s):  
Information Technologies ◽  
Manufacturing Systems ◽  
Rapid Development ◽  
Data Access ◽  
Sensor Data ◽  
False Alarms ◽  
Monitoring And Control ◽  
Stream Data ◽  
Physical Security ◽  
And Control

Abstract With the rapid development of the Internet of Things and information technologies, more and more manufacturing systems become cyber-enabled, which significantly improves the flexibility and productivity of manufacturing. Furthermore, a large variety of online sensors are also commonly incorporated in the manufacturing systems for online quality monitoring and control. However, the cyber-enabled environment may pose the collected online stream sensor data under high risks of cyber-physical attacks as well. Specifically, cyber-physical attacks could occur during the manufacturing process to maliciously tamper the sensor data, which could result in false alarms or failures of anomaly detection. In addition, the cyber-physical attacks may also illegally access the collected data without authorization and cause leakage of key information. Therefore, it becomes critical to develop an effective approach to protect online stream data from these attacks so that the cyber-physical security of the manufacturing systems could be assured. To achieve this goal, an integrative blockchain-enabled method, is proposed by leveraging both asymmetry encryption and camouflage techniques. A real-world case study that protects cyber-physical security of collected stream data in additive manufacturing is provided to demonstrate the effectiveness of the proposed method. The results demonstrate that malicious tampering could be detected in a relatively short time and the risk of unauthorized data access is significantly reduced as well.

Wireless Data Transfer in under Water System

2017 ◽  
Author(s):  
S. Sangeetha ◽  
Santhi Priya ◽  
K. S. Saranya ◽  
S. Saranya ◽  
T. Jayasimha
Keyword(s):  
Data Transfer ◽  
Water System ◽  
Wireless Data

scholarly journals Anomaly Detection in Medical Wireless Sensor Networks using SVM and Linear Regression Models

2014 ◽  
Vol 5 (1) ◽  
pp. 20-45 ◽  
Author(s):  
Osman Salem ◽  
Alexey Guerassimov ◽  
Ahmed Mehaoua ◽  
Anthony Marcus ◽  
Borko Furht
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Anomaly Detection ◽  
Patient Data ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Smart Devices ◽  
Support Vector ◽  
Processing Unit

This paper details the architecture and describes the preliminary experimentation with the proposed framework for anomaly detection in medical wireless body area networks for ubiquitous patient and healthcare monitoring. The architecture integrates novel data mining and machine learning algorithms with modern sensor fusion techniques. Knowing wireless sensor networks are prone to failures resulting from their limitations (i.e. limited energy resources and computational power), using this framework, the authors can distinguish between irregular variations in the physiological parameters of the monitored patient and faulty sensor data, to ensure reliable operations and real time global monitoring from smart devices. Sensor nodes are used to measure characteristics of the patient and the sensed data is stored on the local processing unit. Authorized users may access this patient data remotely as long as they maintain connectivity with their application enabled smart device. Anomalous or faulty measurement data resulting from damaged sensor nodes or caused by malicious external parties may lead to misdiagnosis or even death for patients. The authors' application uses a Support Vector Machine to classify abnormal instances in the incoming sensor data. If found, the authors apply a periodically rebuilt, regressive prediction model to the abnormal instance and determine if the patient is entering a critical state or if a sensor is reporting faulty readings. Using real patient data in our experiments, the results validate the robustness of our proposed framework. The authors further discuss the experimental analysis with the proposed approach which shows that it is quickly able to identify sensor anomalies and compared with several other algorithms, it maintains a higher true positive and lower false negative rate.

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