Academic literature on the topic 'Ibm cloud bluemix'

Sistem keamanan rumah merupakan implementasi yang harus dilakukan untuk meningkatkan keamanan dari kejadian yang tidak diinginkan. Beberapa implementasi hanya memberikan notifikasi sederhana berupa alarm dan tidak menjadi bukti yang kuat apabila terjadi pencurian. Salah satu solusi yang dilakukan adalah penempatan kamera untuk memantau keamanan rumah secara real time diintegrasikan dengan penyimpanan cloud. Bluemix merupakan salah satu provider untuk aplikasi cloud yang memiliki layanan pengolahan dan penyimpanan data, akses aplikasi mobile, pengawasan serta Internet of Things (IoT). Sistem yang diimplementasikan adalah integrasi Raspberry Pi dengan layanan Bluemix untuk melakukan pengawasan keamanan rumah dan memberikan notifikasi kepada pengguna. Sistem mendeteksi jarak menggunakan sensor HC-SR04 terhadap objek dan apabila jarak melewati acuan, hal tersebut adalah indikasi terjadinya pencurian. Berikutnya sistem akan menyalakan buzzer sebagai keluaran suara dan mengaktifkan kamera untuk mengambil gambar lalu diunggah ke object storage Bluemix. Langkah berikutnya yaitu layanan IBM push notification memberikan notifikasi ke perangkat Android pengguna. Pengujian dilakukan dengan menghalangi pembacaan sensor sehingga terjadi indikasi pencurian. Hasilnya adalah sistem berhasil menyalakan buzzer, mengambil gambar lalu diunggah ke Bluemix, dan notifikasi berhasil masuk pada Android. Notifikasi diterima oleh file browser pada perangkat Android dan dilakukan sinkronisasi dengan object storage untuk melakukan pengunduhan berkas gambar yang telah diunggah sebelumnya.Kata kunci: Bluemix, Raspberry Pi, object sorage, IBM push notification Home security system is an implementation that needs to be done to improve the security of unwanted events. Some implementations only provide a simple notification such as alarm and cannot become strong evidence in case of theft. One of the solutions is camera placement to monitor home security in real time integrated with cloud storage. Bluemix is a provider for cloud applications that have data processing and storage services, mobile application access, monitoring and Internet of Things (IoT). System implemented was integration of Raspberry Pi with Bluemix services to conduct home security surveillance and provide notification to user. System detected distance using HC-SR04 sensor to object and if distance passes the reference, it was an indication of theft. Next, system will turned on buzzer as a sound output and activating the camera to take picture and uploaded to Bluemix Object Storage. Next step was IBM push notification service giving notification to user's Android device. The testing was done by blocking the sensor readings so that there was an indication of theft. The result was system succeeded in turning on the buzzer, taking pictures, uploading pictures to Bluemix, and notification successfully logged on Android. Notifications are received by the file browser on Android device and synchronized with object storage to download image files that have been uploaded previously.Keywords: Bluemix, Raspberry Pi, object storage, IBM push notification

In the Industry 4.0 the communication infrastructure is derived from the Internet of Things (IoT), and it is called Industrial IoT or IIoT. Smart objects deployed on the field collect a large amount of data which is stored and processed in the Cloud to create innovative services. However, differently from most of the consumer applications, the industrial scenario is generally constrained by time-related requirements and its needs for real-time behavior (i.e., bounded and possibly short delays). Unfortunately, timeliness is generally ignored by traditional service provider, and the Cloud is treated as a black box. For instance, Cloud databases (generally seen as “Database as a service”—DBaaS) have unknown or hard-to-compare impact on applications. The novelty of this work is to provide an experimental measurement methodology based on an abstract view of IIoT applications, in order to define some easy-to-evaluate metrics focused on DBaaS latency (no matter the actual implementation details are). In particular, the focus is on the impact of DBaaS on the overall communication delays in a typical IIoT scalable context (i.e., from the field to the Cloud and the way back). In order to show the effectiveness of the proposed approach, a real use case is discussed (it is a predictive maintenance application with a Siemens S7 industrial controller transmitting system health status information to a Cloudant DB inside the IBM Bluemix platform). Experiments carried on in this use case provide useful insights about the DBaaS performance: evaluation of delays, effects of involved number of devices (scalability and complexity), constraints of the architecture, and clear information for comparing with other implementations and for optimizing configuration. In other words, the proposed evaluation strategy helps in finding out the peculiarities of Cloud Database service implementations.

Indian economy majorly depends on the agriculture sector hence it is known as the backbone of India. Here agriculture segment accounts for 18% of India’s GDP and is providing employment to 50% of the country workforce. The main aim of this work is to reduce the manual monitoring of soil testing and plant irrigation and help farmers in increasing the agricultural production. The testing of soil is done through various sensors and based on the data received the farmers can cultivate the appropriate crop that is suitable for soil. Detection of plant’s diseases is done through image processing technique. And also includes pest detection and control by using Acoustic sensor and we make use of Ultrasonic sound emitter to keep the pests away from destroying the crops. It alerts farmers through a message. All the information is sent to IBM Bluemix Cloud by ZigBee protocol. A direct communication link is set up between farmers and the consumers without the involvement of any middleman via mobile app.

Nowadays, prolonged sitting among office workers is a widespread problem, which is highly related to several health problems. Many proposals have been reported and evaluated to address this issue. However, motivating and engaging workers to change health behavior to a healthier working life is still a challenge. In this project, a specific application has been deployed for real-time monitoring and alerting office workers for prolonged sitting. The proposed system consists of three distinct parts: The first one is an android smartwatch, which was used to collect sensor data e.g., accelerometer and gyro data, with a custom android wear app. The second one is an android application, which was developed to act as a gateway for receiving the smartwatch’s data and sending them to IBM Bluemix cloud with MQTT protocol. The final part is a Node-Red cloud application, which was deployed for storing, analyzing and processing of the sensor data for activity detection i.e., sitting or walking/standing. The main purpose of the last one was to return relevant feedback to the user, while combining elements from gaming contexts (gamification methods), for motivating and engaging office workers to a healthier behavior. The system was firstly tested for defining appropriate accelerometer thresholds to five participants (control group), and then evaluated with five different participants (treatment group), in order to analyze its reliability for prolonged sitting detection. The results showed a good precession for the detection. No confusing between sitting and walking/standing was noticed. Communication, storage and analysis of the data was successfully done, while the push notifications to the participants, for alerting or rewarding them, were always accurate and delivered on time. Every useful information was presented to the user to a web-based dashboard accessed through a smartphone, tablet or a PC.     The proposed system can easily be implemented at a real-life scenario with office workers. Certainly, there is a lot space for improvement, considering mostly the type of data registered at the system, the method for sitting detection, and the user interface for presenting relevant information.
Numera är förlängt sittande bland kontorsarbetare ett utbrett problem som är väldigt relaterat till flera hälsoproblem. Många förslag har rapporterats och utvärderas för att ta itu med denna fråga. Tydligen är det fortfarande en utmaning att motivera och engagera arbetstagare för att förändra deras hälsobeteende till hälsosammare arbetsliv. I detta projekt har en särskild applikation använts för realtidsövervakning och varnar kontorsarbetare för förlängt sittande. Det föreslagna systemet består av tre olika delar: Den första är en android smartwatch, som användes för att samla sensordata t.ex. accelerometer och gyrodata, med en anpassad android wear app. Den andra är en en androidapplikation som fungerade som en gateway för att ta emot smartwatchens data och skickar datan till IBM Bluemix-Cloud med MQTT-protokollet. Den sista delen är en Node-RED Cloud-Applikation som användes för lagring, analysering och behandling av sensordata för aktivitetsdetektering. Detta innebär sittande eller gå/stående med det huvudsakliga ändamålet att returnera relevant återkoppling till användaren, samtidigt som man kombinerar element från spelkontekster (gamification metoder), för att motivera och engagera arbetarna till ett hälsosammare beteende. Systemet testades först för att definiera lämpliga accelerometertrösklar till fem deltagare (kontroll grupp) och utvärderades sedan med fem olika deltagare (behandingsgrupp) för att analysera dess tillförlitlighet för långvarig sittdetektering. Resultaten visade en bra precession för detektionen. Ingen förvirring mellan att sitta och gå / stående märktes. Kommunikation, lagring och analys av data gjordes framgångsrikt, medan push-meddelandena till deltagarna, för att varna eller belöna dem, var alltid korrekta och levererade i tid. All användbar information presenterades för användaren på en webbaserad dashboard som nås via en smartphone surfplatta eller en dator. Det föreslagna systemet kan enkelt implementeras i ett verkligt scenario med kontorsarbetare. Visst finns det mycket utrymme för förbättring om man tänker på majoriteten av data som registrerats i systemet, metoden för sittande detektion och användargränssnittet för presentering av relevant information.

This work is developed on the basis of data related to the driving experience of a motorcycle in its aspects. The drivers point of view is supported by the analysis of the data produced by the sensors and collected by a data logger. The two aspects, human and technical, have been standardized from a technological point of view so that they can be analysed and related to each other. The need for cognitive algorithms has led to the use of Cloud PaaS and SaaS technologies: these have allowed the rapid realization of the project without technical constraints. All of this is part of the specific requirements set up by Ducati's PQ department whose aim is to evaluate the response on the road of new models or technological improvements before the production in series. The final solution for the proposed data collection was realized using different services of IBM Cloud: a web app was built using a virtual assistant based on cognitive technology that guides the user in the collection of information and verifies its consistency. The application required backend services such as an Object Storage and a Database, to store multimedia content and data respectively. Concerning the front-end instead, the automation of the collection mode has led to the introduction of an acquisition process that was easier to use and always available in terms of reachability and flexibility. The information related to the data collected by the logger did not need to be mediated by further technological components. The technology used for the analytical part is Microsoft's Power BI. The integration with the two data sources is plug and play: the data are automatically updated. Several types of analysis have been done and range from reconstruction and correlation of measurements on a route to text analysis of driver sensations. In addition to this, a PCB has been developed to solve an issue related to the data logger itself.