Relevant bibliographies by topics / IBM Bluemix

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'IBM Bluemix'

Author: Grafiati
Published: 4 June 2021
Last updated: 4 February 2022

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Journal articles on the topic "IBM Bluemix"

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Gheith, A., R. Rajamony, P. Bohrer, et al. "IBM Bluemix Mobile Cloud Services." IBM Journal of Research and Development 60, no. 2-3 (2016): 7:1–7:12. http://dx.doi.org/10.1147/jrd.2016.2515422.

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Rahmatullah, Griffani Megiyanto, Muhammad Ayat, and Wirmanto Suteddy. "Sistem Anti Maling Untuk Rumah Tinggal Menggunakan IoT Bluemix." Jurnal Teknologi Rekayasa 3, no. 1 (2018): 55. http://dx.doi.org/10.31544/jtera.v3.i1.2018.55-62.

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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
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COLLINÁSZY, Juraj, Marek BUNDZEL, and Iveta ZOLOTOVÁ. "IMPLEMENTATION OF INTELLIGENT SOFTWARE USING IBM WATSON AND BLUEMIX." Acta Electrotechnica et Informatica 17, no. 1 (2017): 58–63. http://dx.doi.org/10.15546/aeei-2017-0008.

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Kim, M., A. Mohindra, V. Muthusamy, et al. "Building scalable, secure, multi-tenant cloud services on IBM Bluemix." IBM Journal of Research and Development 60, no. 2-3 (2016): 8:1–8:12. http://dx.doi.org/10.1147/jrd.2016.2516942.

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Alhirabi, Nada, Omer Rana, and Charith Perera. "Security and Privacy Requirements for the Internet of Things." ACM Transactions on Internet of Things 2, no. 1 (2021): 1–37. http://dx.doi.org/10.1145/3437537.

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The design and development process for internet of things (IoT) applications is more complicated than that for desktop, mobile, or web applications. First, IoT applications require both software and hardware to work together across many different types of nodes with different capabilities under different conditions. Second, IoT application development involves different types of software engineers such as desktop, web, embedded, and mobile to work together. Furthermore, non-software engineering personnel such as business analysts are also involved in the design process. In addition to the complexity of having multiple software engineering specialists cooperating to merge different hardware and software components together, the development process requires different software and hardware stacks to be integrated together (e.g., different stacks from different companies such as Microsoft Azure and IBM Bluemix). Due to the above complexities, non-functional requirements (such as security and privacy, which are highly important in the context of the IoT) tend to be ignored or treated as though they are less important in the IoT application development process. This article reviews techniques, methods, and tools to support security and privacy requirements in existing non-IoT application designs, enabling their use and integration into IoT applications. This article primarily focuses on design notations, models, and languages that facilitate capturing non-functional requirements (i.e., security and privacy). Our goal is not only to analyse, compare, and consolidate the empirical research but also to appreciate their findings and discuss their applicability for the IoT.
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Ferrari, Paolo, Emiliano Sisinni, Alessandro Depari, et al. "On the Performance of Cloud Services and Databases for Industrial IoT Scalable Applications." Electronics 9, no. 9 (2020): 1435. http://dx.doi.org/10.3390/electronics9091435.

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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.
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Sarosa Castrena Abadi, Muhammad Ayat Hidayat, and Purwandito Tulus Asmoro. "SISTEM REKOMENDASI FILM BERBASIS JEJARING SOSIAL (TWITTER) MENGGUNAKAN IBM BLUEMIX." Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) 5, no. 1 (2020). http://dx.doi.org/10.20527/jtiulm.v5i1.45.

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Perkembangan industri hiburan seperti film saat ini sangat begitu pesat dan bervariasi, hal tersebut seringkali membingungkan para penikmat film dalam menentukan film yang sangat direkomendasikan, solusi atas permasalahan tersebut adalah suatu sistem rekomendasi film yang dapat memberikan rekomendasi film-film yang berkualitas untuk ditonton oleh penikmat film berdasarkan rating film tersebut.
 Twitter jejaring sosial favorit yang masih sering digunakan oleh masyarakat saat ini untuk menuliskan pikiran, perasaan maupun aspirasi dari setiap user, pada sistem ini cuitan twitter berfungsi sebagai data input yang dapat diolah menjadi suatu data yang lebih bernilai seperti rating. Penelitian ini dibahas sistem rekomendasi film berdasarkan rating dari komentar - komentar twitter menggunakan ibm bluemix dengan algoritma Support Vector Machine. Hasil Pengujian memberikan keluaran berupa rating, dimana nilai yang dihasilkan cenderung mendekati nilai rating dari situs rating film yang sudah popular dan terpercaya.
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Sukesh, Manyam, R. Naveen Kumar, and C. Lokanatha Reddy. "Development and deployment of real-time cloud applications on red hat OpenShift and IBM bluemix." Materials Today: Proceedings, April 2021. http://dx.doi.org/10.1016/j.matpr.2021.01.458.

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"Modern Agriculture using Wireless Sensor Network." International Journal of Recent Technology and Engineering 8, no. 5 (2020): 201–5. http://dx.doi.org/10.35940/ijitee.d9098.029420.

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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.
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Patel, Divyesh, Arpita Shah, and Hetal Shah. "An IoT Enabled Worker Safety System Using Gas and Temperature System." International Journal of Scientific Research in Computer Science, Engineering and Information Technology, September 30, 2019, 139–43. http://dx.doi.org/10.32628/cseit195527.

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This paper aims to build up a model for an online remote gas and temperature checking device for worker’s safety in sewage pipelines. The device is WSN based microcontroller equipped with analog and digital sensor. The design included several units mainly: Arduino Microcontroller MQ-135, DHT11, Gas and Temperature Sensors, and the current regulator circuit. The sensors are connected with a microcontroller through an ADC for advanced flag change and information logging. An LCD show is likewise associated with the microcontroller to show the estimations. For examination and filing purposes, the information can be exchanged to a PC with a graphical UI program through a USB interface. The device displays toxic gas and workers real-time position, transmit information remotely via a graphical user interface to IBM bluemix provide adjacent help. By keeps observing, this model will prone to diminish mishaps and slowly spares an existence. The model has numerous points of interest when contrasted with other checking frameworks as far as its littler size, gigantic memory limits, on-gadget show, bring down cost and more noteworthy versatility.
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Dissertations / Theses on the topic "IBM Bluemix"

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Ho, Hong. "Utvärdering av användbarhet hos molntjänstplattformen Bluemix från IBM." Thesis, Karlstads universitet, Handelshögskolan, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-43311.

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Många studenter behöver en web-baserad tjänst som de kan uppnå målet inom sina studier. Många studenter inom IT-området måste ladda ner mängder av programvaror och satsa relativt mycket pengar på sina datorer för att ha tillräckligt utrymme och processorkraft att köra olika program under sin studietid. Studenterna behöver en smidig, mångsidig och flexibel internetbaserad plattform som de kan komma åt när som helst, var som helst och från vilken enhet som helst. Dessutom är användbarhet hos plattformen en viktig aspekt för att supportera studenternas arbete. Bluemix är en Plattform as a Service (PaaS) - en typ av molntjänst. På Bluemix kan människor inom IT-området skapa, ändra, uppdatera och lagra sina applikationer med olika programmeringsspråk och de kan lägga olika tjänster till sina applikationer smidigt och snabbt. Syftet med den här uppsatsen är att utvärdera användbarhet av molntjänstplattformen Bluemix och undersöka vilken nytta som användare kan få när de använder plattformen. Den huvudsakliga målgruppen utgör studenter inom IT-området. Data har samlats in med hjälp av olika tekniker till exempel användartester, observation, tänka-högt (Think Aloud), intervju och enkät. Undersökningen visar att molntjänstplattformen Bluemix har god användbarhet fastän det finns några punkter som inte följer principer för god användbarhet. Dessutom är den en plattform som många testpersoner (studenter) önskar kan användas på universitetet. Nyckelord: Användbarhet, molntjänst, PaaS, SaaS, Bluemix, designprinciper, användartester, ITutbildning
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Lind, Patric. "Evaluation of IBM Bluemix (PaaS) auto-scaling service for microservices." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-395881.

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The company Sisyfos Digital AB host some of their solution on the cloud, and have expressed an interest in scaling their applications. The ability to scale applications can be an important factor to achieve high availability, and therefore led to questions such as in what extent is this possible and efficient for different applications. Using a service for scaling on this cloud infrastructure, testing with multiple applications and varying incoming requests, the goal was evaluate benchmarks and identify bottlenecks for incoming requests with its response time. The results show that depending on the application, scaling can be a valuable tool under the right prerequisites. Some of these prerequisites need to be evaluated beforehand, and the successfulness of the scaling is dependent on it. Under the right conditions, an almost linear result can be achieved when scaling between one and three instances. However, the most significant aspect of scaling is the identification of bottlenecks in the application.
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Åström, Gustav. "Kognitiva tjänster på en myndighet : Förstudie om hur Lantmäteriet kan tillämpa IBM Watson." Thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-30902.

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Many milestones have been passed in computer science and currently we are on our way to pass yet another: artificial intelligence. One of the characteristics of AI is to be able to interpret so-called unstructured data, i.e., data that lacks structure. Unstructured data can be useful and with the new tools within AI is it possible to interpret it and use it to solve problems. This has the potential to be useful in practical applications such as processing and decision support. The work has been done at Apendo AB, which has the Swedish National Land Survey as a customer. The work is to investigate how AI-driven cognitive services through IBM Watson can be applied to the Swedish National Land Survey. The goal is to answer the following questions: Is it possible to apply cognitive services through Watson's services to give decision support to the Swedish National Land Survey already? In what ways can you use Watson's services to create a decision support? How effective can the solution for the Swedish National Land Survey be, i.e. how much time and costs can they save by using Watson's services on the chosen concept? As a practical part of the AI study, a perceptron was developed and evaluated. Through an agile approach, tests and studies about IBM Watson have taken place in parallel with interviews with employees at the Swedish National Land Survey. The tests were performed in the PaaS service IBM Bluemix with both Node-RED and an own built web application. Though the interviews, the Watson service Retrieve and Rank became interesting and examined more closely. With Retrieve and Rank you can get questions answered by ranking selected corpus pieces that are then trained for better answers. Uploading the corpus with related questions resulted in that 75% of the questions was answered correctly. Applications for the Swedish National Land Survey can then be a cognitive search function that helps administrators to search information in manuals and the law book.<br>Många milstolpar har passerats inom datavetenskapen och just nu håller vi på att passera en till: artificiell intelligens. En av de egenskaper som kännetecknar AI är att kunna tolka s.k. ostrukturerad data, alltså sådan data som saknar struktur. Ostrukturerad data vara användbar och med de nya verktygen inom AI är det möjligt att tolka för sedan använda det till att lösa problem. Detta har potential att vara användbart inom praktiska applikationer såsom handläggning och beslutsstöd. Arbetet har skett på företaget Apendo AB som har Lantmäteriet som kund. Arbetet går ut på att undersöka hur AI-drivna kognitiva tjänster genom IBM Watson kan tillämpas på Lantmäteriet. Målet är att besvara följande frågor: Är det möjligt att tillämpa kognitiva tjänster genom Watsons tjänster för att ge beslutsstöd åt Lantmäteriet redan i dagsläget? På vilka sätt kan man använda Watsons tjänster för att skapa ett beslutsstöd? Hur effektiv kan lösningen för Lantmäteriet bli, d.v.s. hur mycket tid och kostnader kan de tänkas spara genom att använda Watsons tjänster på valt koncept? Som praktisk del av studien om AI utvecklades och utvärderades en perceptron. Genom ett agilt förhållningssätt har tester och studier om IBM Watson skett parallellt med intervjuer med anställda på Lantmäteriet. Testerna utfördes i PaaS-tjänsten IBM Bluemix med både Node- RED och egenbyggd webbapplikation. Av intervjuerna blev Watson-tjänsten Retrieve and Rank intressant och undersöktes noggrannare. Med Retrieve and Rank kan man få frågor besvarade genom rankning av stycken av valt korpus som sedan tränas upp för bättre svar. Uppladdning av korpus med tillhörade frågor gav att 75 % av frågorna besvarades korrekt. Tillämpningarna Lantmäteriet kan då vara en kognitiv uppträningsbar sökfunktion som hjälper handläggare att söka information i handböcker och lagboken.
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Charalampidis, Vasileios. "Real-Time Monitoring System of Sedentary Behavior with Android Wear and Cloud Computing : An office case study." Thesis, KTH, Skolan för teknik och hälsa (STH), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-210017.

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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.<br>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.
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Ceccarelli, Viviana. "Data Logger: cognitive analysis." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.

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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.
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Book chapters on the topic "IBM Bluemix"

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Lirathni, Hamadi, Amira Zrelli, Med Hchemi Jridi, and Tahar Ezzedine. "A Real-Time Flash-Floods Alerting System Based on WSN and IBM Bluemix Cloud Platform." In Smart Innovation, Systems and Technologies. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21009-0_38.

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Biondi, Giulio, Valentina Franzoni, and Valentina Poggioni. "A Deep Learning Semantic Approach to Emotion Recognition Using the IBM Watson Bluemix Alchemy Language." In Computational Science and Its Applications – ICCSA 2017. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62398-6_51.

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"The IBM Bluemix Buildpack for Swift." In Swift in the Cloud. John Wiley & Sons, Inc., 2017. http://dx.doi.org/10.1002/9781119368502.ch4.

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Conference papers on the topic "IBM Bluemix"

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Cacais, Michelle, Danielo G. Gomes, Paulo Armando C. Aguilar, and Rossana M. C. Andrade. "Performance Evaluation of Wearable Computing Frameworks." In XVI Workshop em Desempenho de Sistemas Computacionais e de Comunicação. Sociedade Brasileira de Computação - SBC, 2017. http://dx.doi.org/10.5753/wperformance.2017.3354.

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Internet of Things (IoT) aims to connect multiple devices and enable communication on a global scale. In this context, wearable computing turns into one of the most imperative technologies for data capture and transfer. Even though many solutions exist for fast development of wearable applications, it is difficult to know which one is the best for each situation. In this paper, we evaluated the performance of three wearable computing frameworks: SPINE, BNSM and IBM Bluemix. We used performance metrics such as data accuracy, memory footprint and energy consumption in a movement recognition scenario. Results have shown that, among the analyzed frameworks, (i) BNSM is the best one concerning energy-efficiency; (ii) IBM Bluemix is the best one for data accuracy. Both frameworks presented interesting results in terms of memory footprint.
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Husni, Emir, Galuh Boy Hertantyo, Daniel Wahyu Wicaksono, Faisal Candrasyah Hasibuan, Andri Ulus Rahayu, and Muhamad Agus Triawan. "Applied Internet of Things (IoT): Car monitoring system using IBM BlueMix." In 2016 International Seminar on Intelligent Technology and Its Applications (ISITIA). IEEE, 2016. http://dx.doi.org/10.1109/isitia.2016.7828696.

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Popov, Aleksey, Andrey Proletarsky, Sergey Belov, and Alexander Sorokin. "Fast Prototyping of the Internet of Things solutions with IBM Bluemix." In Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences, 2017. http://dx.doi.org/10.24251/hicss.2017.126.

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David, Valerie, Harini Ragu, Rohith Kanna Duraiswamy, and Sasikumar P. "IoT based Automated Indoor Agriculture System Using Node-RED and IBM Bluemix." In 2021 6th International Conference on Inventive Computation Technologies (ICICT). IEEE, 2021. http://dx.doi.org/10.1109/icict50816.2021.9358672.

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Al-Maliky, Rusul S. B. "A Semantic Approach to Emotion Recognition Using IBM Watson Bluemix tone Analyzer and translator Language." In 2019 2nd International Conference on Engineering Technology and its Applications (IICETA). IEEE, 2019. http://dx.doi.org/10.1109/iiceta47481.2019.9012970.

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Mehmood, Mussawir Ul, Waleed Ali, Abasin Ulasyar, Haris Sheh Zad, Abraiz Khattak, and Kashif Imran. "A Low Cost Internet of Things (LCIoT) Based System for Monitoring and Control of UPS System using Node-Red, CloudMQTT and IBM Bluemix." In 2019 International Conference on Electrical, Communication, and Computer Engineering (ICECCE). IEEE, 2019. http://dx.doi.org/10.1109/icecce47252.2019.8940686.

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Xiao, Jin, and John Rofrano. "Managing vulnerabilities in a cloud native world with bluefix." In 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM). IEEE, 2017. http://dx.doi.org/10.23919/inm.2017.7987368.

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