scholarly journals Development and Implementation of an OpenSource IoT Platform, Network and Data Warehouse for Privacy-Compliant Applications in Research and Industry

2021 ◽  
Vol 7 (2) ◽  
pp. 507-510
Author(s):  
Sebastian Stadler ◽  
Eduardo Romero Borrero ◽  
Johannes Zauner ◽  
Christian Hanshans
Keyword(s):  
Data Acquisition ◽  
Data Privacy ◽  
Industrial Applications ◽  
Visual Programming ◽  
Ease Of Use ◽  
Raspberry Pi ◽  
Sensors And Actuators ◽  
Research Activities ◽  
Machine Communication ◽  
User Friendly

Abstract In the scientific field, data acquisition using commercial or self-developed sensors is a necessity for many research activities. Data security and data privacy are important requirements in all types of IoT applications, especially in the medical context. IoTree42 is a powerful, OpenSource platform that closes the gap between cost-efficiency, the ease of use and digital sovereignty. The flexible and user-friendly design makes the platform ideal for the originally conceived research context. Nevertheless, it can be used for smaller budget-oriented setups and industrial applications with thousands of sensors and actuators likewise. The platform was developed with security in mind by minimizing interfaces and the use of stable software components and transport protocols. IoTree42 utilizes lightweight OpenSource software cast into a flexible backend, allowing the deployment not only on full-fledged servers but also on single board computers like the Raspberry Pi. Data is transmitted with low overhead via MQTT, a robust protocol optimized for machine to machine communication. The transmission technology between all components is freely selectable. Besides data acquisition, IoTree42 enables control of actuators and automation through interfaces with visual programming tools. This allows for remote interventions without requiring prior programming experience. The incoming data can conveniently be visualized in dashboards or easily be exported for further analysis. The network consists of a central server and satellites (gateways) arranged in a star topology. Sensors and actuators connect to the gateway. The initial setup of the server and the gateways is automated, well documented, and can be done within minutes. Thanks to the increasing usage and the contribution of the community, the pool of code examples for sensors is growing and lowers the entry hurdle for users without programming background. IoTree42 is a fast-growing, multi-user, hardware and cloud agnostic, easy to deploy, privacy compliant and competitive solution compared to commercial IoT alternatives.

scholarly journals An IoT-Based Smart Home Automation System

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3784
Author(s):  
Cristina Stolojescu-Crisan ◽  
Calin Crisan ◽  
Bogdan-Petru Butunoi
Keyword(s):  
Application Programming Interface ◽  
Smartphone Application ◽  
Raspberry Pi ◽  
Automation System ◽  
Home Automation ◽  
Network Connection ◽  
Communication Scheme ◽  
Application Programming ◽  
Home Automation System ◽  
User Friendly

Home automation has achieved a lot of popularity in recent years, as day-to-day life is getting simpler due to the rapid growth of technology. Almost everything has become digitalized and automatic. In this paper, a system for interconnecting sensors, actuators, and other data sources with the purpose of multiple home automations is proposed. The system is called qToggle and works by leveraging the power of a flexible and powerful Application Programming Interface (API), which represents the foundation of a simple and common communication scheme. The devices used by qToggle are usually sensors or actuators with an upstream network connection implementing the qToggle API. Most devices used by qToggle are based on ESP8266/ESP8285 chips and/or on Raspberry Pi boards. A smartphone application has been developed that allows users to control a series of home appliances and sensors. The qToggle system is user friendly, flexible, and can be further developed by using different devices and add-ons.

Face recognition in an intelligent door lock with ResNet model based on deep learning

2021 ◽  
pp. 1-11
Author(s):  
Suphawimon Phawinee ◽  
Jing-Fang Cai ◽  
Zhe-Yu Guo ◽  
Hao-Ze Zheng ◽  
Guan-Chen Chen
Keyword(s):  
Face Recognition ◽  
Detection System ◽  
Low Cost ◽  
Ease Of Use ◽  
Raspberry Pi ◽  
Training Methods ◽  
Graphics Recognition ◽  
Face Images ◽  
The Face ◽  
Door Lock

Internet of Things is considerably increasing the levels of convenience at homes. The smart door lock is an entry product for smart homes. This work used Raspberry Pi, because of its low cost, as the main control board to apply face recognition technology to a door lock. The installation of the control sensing module with the GPIO expansion function of Raspberry Pi also improved the antitheft mechanism of the door lock. For ease of use, a mobile application (hereafter, app) was developed for users to upload their face images for processing. The app sends the images to Firebase and then the program downloads the images and captures the face as a training set. The face detection system was designed on the basis of machine learning and equipped with a Haar built-in OpenCV graphics recognition program. The system used four training methods: convolutional neural network, VGG-16, VGG-19, and ResNet50. After the training process, the program could recognize the user’s face to open the door lock. A prototype was constructed that could control the door lock and the antitheft system and stream real-time images from the camera to the app.

scholarly journals BlocklyXR: An Interactive Extended Reality Toolkit for Digital Storytelling

2021 ◽  
Vol 11 (3) ◽  
pp. 1073
Author(s):  
Kwanghee Jung ◽  
Vinh T. Nguyen ◽  
Jaehoon Lee
Keyword(s):  
Technology Acceptance ◽  
Digital Storytelling ◽  
Visual Programming ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Programming Approach ◽  
Intention To Use ◽  
Perceived Ease Of Use ◽  
Positive Effects ◽  
Block Based

Traditional in-app virtual reality (VR)/augmented reality (AR) applications pose a challenge of reaching users due to their dependency on operating systems (Android, iOS). Besides, it is difficult for general users to create their own VR/AR applications and foster their creative ideas without advanced programming skills. This paper addresses these issues by proposing an interactive extended reality toolkit, named BlocklyXR. The objective of this research is to provide general users with a visual programming environment to build an extended reality application for digital storytelling. The contextual design was generated from real-world map data retrieved from Mapbox GL. ThreeJS was used for setting up, rendering 3D environments, and controlling animations. A block-based programming approach was adapted to let users design their own story. The capability of BlocklyXR was illustrated with a use case where users were able to replicate the existing PalmitoAR utilizing the block-based authoring toolkit with fewer efforts in programming. The technology acceptance model was used to evaluate the adoption and use of the interactive extended reality toolkit. The findings showed that visual design and task technology fit had significantly positive effects on user motivation factors (perceived ease of use and perceived usefulness). In turn, perceived usefulness had statistically significant and positive effects on intention to use, while there was no significant impact of perceived ease of use on intention to use. Study implications and future research directions are discussed.

scholarly journals From big data to bedside decision-making: the case for AdverseEvents

2013 ◽  
Vol 3 (1) ◽  
pp. 3
Author(s):  
Giuseppe Biondi Zoccai ◽  
Elena Cavarretta ◽  
Giacomo Frati
Keyword(s):  
Decision Making ◽  
Clinical Evidence ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Ease Of Use ◽  
Antithrombotic Agent ◽  
Post Marketing ◽  
The Individual ◽  
User Friendly ◽  
Based Medicine

<p>Evidence-based medicine has gained mainstream popularity, but it requires a delicate balance between clinical evidence, physician skills, patient preferences, and costs. Facing the individual patient, even a simple decision such as which antithrombotic agent should be prescribed becomes complex. There are several reasons for this conundrum, but one of the foremost is the limited external validity of pivotal randomized trials, with their extremely restrictive selection criteria. Post-marketing reporting of adverse events is a very useful and democratic means to appraise the risk-benefit profile, but to date such reports were not organized or available. The development of the Food and Drug Administration (FDA) venue for such task, the FDA Adverse Event Reporting System (FAERS) has substantially improved data collection. However, analysis of this extensive relational database remains complex for most but few companies or agencies. AdverseEvents is a novel online platform enabling updated and user-friendly inquiry of FAERS. Given its ease of use, flexibility and comprehensiveness, it is likely going to improve decision making for healthcare authorities and practitioners, as well as patients. This is clearly testified by the precise and informative comparative analysis that can be performed with AdverseEvents on novel antithrombotic agents.</p>

scholarly journals Data-Centric Knowledge Discovery Strategy for a Safety-Critical Sensor Application

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Nilamadhab Mishra ◽  
Hsien-Tsung Chang ◽  
Chung-Chih Lin
Keyword(s):  
Knowledge Discovery ◽  
Time Frame ◽  
Industrial Applications ◽  
Sensor Data ◽  
Sensors And Actuators ◽  
Safety Critical ◽  
Sensor Applications ◽  
Hard Time ◽  
Collection Data ◽  
Time Critical

In an indoor safety-critical application, sensors and actuators are clustered together to accomplish critical actions within a limited time constraint. The cluster may be controlled by a dedicated programmed autonomous microcontroller device powered with electricity to perform in-network time critical functions, such as data collection, data processing, and knowledge production. In a data-centric sensor network, approximately 3–60% of the sensor data are faulty, and the data collected from the sensor environment are highly unstructured and ambiguous. Therefore, for safety-critical sensor applications, actuators must function intelligently within a hard time frame and have proper knowledge to perform their logical actions. This paper proposes a knowledge discovery strategy and an exploration algorithm for indoor safety-critical industrial applications. The application evidence and discussion validate that the proposed strategy and algorithm can be implemented for knowledge discovery within the operational framework.

scholarly journals Model Results and Software Comparisons in Myrtle Beach, SC Using Virtual Beach and R Regression Toolboxes

2015 ◽  
pp. 80-85
Author(s):  
Matthew J. Neet ◽  
R. Heath Kelsey ◽  
Dwayne E. Porter ◽  
Dan W. Ramage ◽  
Adrian B. Jones
Keyword(s):  
Environmental Protection Agency ◽  
Ease Of Use ◽  
Statistical Interpretation ◽  
Protection Agency ◽  
R Software ◽  
Robust Model ◽  
Myrtle Beach ◽  
Model Setup ◽  
User Friendly ◽  
Forecast Modeling

Utilizing R software and a variety of data sources, daily forecasts of bacteria levels were developed and automated for beach waters in Myrtle Beach, SC. Modeled results are then shown for beach locations via a website and mobile device app. While R provides a robust set of tools for use in forecast modeling, the software has an extensive learning curve and requires skilled statistical interpretation of results. The Environmental Protection Agency (EPA) created the “Virtual Beach” software package to address these concerns. To evaluate the utility of the more user-friendly Virtual Beach modeling toolbox, predictive models were developed and model results were analyzed using the two software suites. Recommendations were made based on ease of use and several performance measures. Model results indicate the two software toolboxes yield comparable outputs. However, Virtual Beach tends to create more robust model forecasts, while R provides more options for model setup and outputs.

scholarly journals Integration of Blockchain Technology in IoT for High Level Security

2019 ◽  
Vol 8 (10) ◽  
pp. 491-497
Keyword(s):  
Radio Frequency Identification ◽  
Humidity Sensor ◽  
Raspberry Pi ◽  
Distributed Network ◽  
Peer Communication ◽  
Blockchain Technology ◽  
Frequency Identification ◽  
A Chain ◽  
High Level ◽  
Machine Communication

IoT (Internet of Things) made headway from Machine to Machine communication without human intrusion for number of machines to connect with the aid of network. There is esteem; by 2020 there will be 26 times more connected things than people. Hence, the concern of security rises along with the high installments. The BlockChain Technology takes place of all central entities, which is peer to peer communication with the distributed network. In this paper, two Arduino boards as nodes and a Raspberry Pi as server are to be configured to connect to the Wi-Fi using ESP8266(node mc). To make data transmission from the two nodes to server, integration of temperature and humidity sensor in one node and RFID (Radio Frequency Identification) reader in other node is to be done. Data should be in the form of blocks and integration of data is in the form of a chain, forming it a Blockchain. All the blocks are linked in the chain manner of which the current hash of the previous block must match with the previous hash of the next block. Then only the blocks of data are secured. While receiving data every time from nodes to server, the previous hash is to be checked such that the arrival of the information is being verified to know if it’s really genuine. If the cryptographic hash does not match then data manipulation is happened. So, in this paper, we will see, along with how practically the security is highly offered by the blockchain technology and how can we easily identify if the data has been tampered along the way it reaches to us. Henceforth, we will found a way of application to secure our IoT data without any regrets in this paper.

scholarly journals PENERAPAN TECHNOLOGY ACCEPTANCE MODEL PADA KUALITAS USER EXPERIENCE APLIKASI MULTIMEDIA COMPANY PROFILE BPJS KESEHATAN WONOSOBO

Device ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 9-14
Author(s):  
Saifu Rohman
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
User Experience ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Perceived Ease Of Use ◽  
Actual Use ◽  
Acceptance Model ◽  
Behavioral Intention To Use ◽  
User Friendly

Company Profile sebuah perusahaan merupakan sebuah media yang memiliki peran yang sangat penting dalam menunjukkan eksistensinya di dalam berbagai bidang dunia bisnis. Perkembangan dunia teknologi informasi menuntut untuk selalu memberikan sesuatu yang lebih nyaman dan mengedepankan user experience. Metode TAM (Technology Acceptance Model) merupakan salah satu metode yang tepat dalam merancang dan membangun sistem yang user friendly dalam meningkatkan tingkat kepuasan pengguna pada user experience. Dengan mengimplementasikan konstruk-konstruk TAM yang meliputi PU (Perceived Usefulness), PEOU (Perceived Ease of Use), ATU (Attitude Toward Using), BITU (Behavioral Intention to Use) dan AU (Actual Use) maka dapat dipastikan akan meningkatkan tingkat kenyamanan user experience melalui interface yang baik dan sesuai dengan kebutuhan pengguna informasi.

Sign in / Sign up

Export Citation Format

Share Document