Fast Prototyping of the Internet of Things solutions with IBM BluemixAleksey Popov and Andrey ProletarskyBauman Moscow State Technical University,

Moscow, Russiaalexpopov@bmstu.ru, pav@bmstu.ru

Sergey Belov and Alexander SorokinIBM Corporation,

Presnenskaya emb. 5, Moscow, RussiaSergey Belov@ru.ibm.com, alexander sorokin@ru.ibm.com

AbstractFast prototyping for IoT projects has gained attrac-

tion in many industries. Today’s IT market requiresnew faster techniques to get business advantages in dif-ferent industries starting from the energy consumptionand retail to the manufacturing, services, and agricul-ture. Combining sensors and actuators, embedded sys-tems and networks with cloud computing platforms andcognitive services in one project is a very promising ap-proach to address industry needs. Thus, system devel-opers have to be familiar with many design technolo-gies and best practices. At the same time, this approachrequires a profound change in the way of interactionbetween major IoT market actors: suppliers and con-sumers of cloud platfrm and services, teams of devel-opers and universities. In this paper, we analyze howto build effectively interaction of major IoT market ac-tors and discuss a platform for such collaboration. Wepresent a collaborative framework for fast prototypingof IoT solutions with different stakeholders participat-ing. The paper demonstrates the results of this approachin the case of interaction between vendor, university,and industry. We consider a number of technologicaland practical aspects of this collaborative frameworkusing IBM Bluemix cloud platform and IoT templates.We tested this approach in IoT hackathon with a par-ticipation of a vendor, local business partners, and in-dustry representatives. Projects developed during thishackathon will be used to illustrate results achieved byapplying introduced concept for IoT solutions prototyp-ing.

1. Introduction

In order to achieve the sustainable development, hu-manity is now faced with global problems of air and soilcontamination, lack of drinking water, carbon dioxideemissions, the fast growing city population and manyothers. Therefore we need the new powerful concept toimprove and optimize our life everywhere where it ispossible. The Internet of Things as the promising infor-mation technology gives the ability to understand and

control physical processes much better than ever before.The true challenge today is to get maximum value fromthe Internet of Things and Smart technology incorpo-rated into factories, cities, buildings, retail environment,agriculture and healthcare [1].

The IoT is usually defined as the technology to dig-itize and connect everything into computing networks[2]. Billions of physical assets already generating datavolumes twice as fast as social networks and traditionalcomputers [3]. Highly varied and noisy streaming datawith short lifetime make it difficult to implement effec-tive IoT projects in reasonable time. Hence the most IoTdata are not used for an active analytic optimization andcontrol, but for single event detection. To reduce thecomplexity and to release the potential of data analyticand Smart services, the information industry needs toimplement robust cloud technology and cognitive com-puting.

The speed of development is expected to grow signif-icantly, which requires jointly orchestrated efforts of allparties involved. The major resource to increase devel-opment speed is drastically reducing time to prototypethe product while keeping its core analytic functional-ity. Fortunately with new cloud platforms for develop-ers with a rich set of services embedded it now becomespossible to implement a prototype in just a few hours byapplying the new approach, which will be given in lateranalysis.

With great progress made in recent years with scal-able cloud computing, the development paradigm shift-ing from the computation time to the development speedoptimization. The fast-changing market makes time ofdevelopment the most valuable resource than any oth-ers. That means besides other things that the IoT edu-cation should be of more interest in academic world [4].We also believe that universities can play an even moreimportant role in the new technological environment byaddressing new issues which all parties involved in IoTprojects are facing, by testing new frameworks in stu-dent teams projects, hackathons, etc.

The paper is organized as follows. In section 2 wewill consider the production chain for IoT projects andintroduce general collaborative framework. In Section 3

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Proceedings of the 50th Hawaii International Conference on System Sciences | 2017

URI: http://hdl.handle.net/10125/41279ISBN: 978-0-9981331-0-2CC-BY-NC-ND

Figure 1. Internet of Things supply chain

we move on to build a practical template for fast proto-typing of IoT services which will include infrastructurecomponent. In section 4, we’ll give the description ofIoT hackathon at the Technical University. The projectscompleted during a hackathon organized jointly by IBMin Bauman Moscow State Technical University will beshown in section 5. A successful project started duringthis hackathon which was funded by a client right af-ter, will be demonstrated in section 6. In section 7, wepresent the conclusions and discuss next steps.

2. Problem Definition

We define four actors in the IoT supply chain: acloud service company (i); universities or academictechnology centers (ii); creative development teams orindividuals (iii); and customers (iv). Figure 1 shows thebasic concept of an IoT supply chain interactions: theclockwise process of experience movement goes fromcloud service company to customers (i); and the counter-clockwise process of technology movement - from cus-tomers to cloud service company(ii). While this area isrelatively new for the research, we discuss some relatedworks.

The IoT supply chain can be defined as an intelli-gent interconnected network that binds together multi-ple tiers of suppliers, contract manufacturers, serviceproviders, distributors and customers, physically locatedacross different regions of the world [5]. By improv-ing the entire supply chain efficiency all trading partnerswill greatly increase the economic benefit [6]. Takinginto account the important role of universities and thesustainable technologies improvement we revise this ap-proach with the IoT supply chain (as it depicted in Fig-ure 1).

To make profitable business long term, major play-

ers in cloud market should create an active ecosystem ofdevelopment teams across the globe. Therefore, cloudenterprises have to collaborate with universities to pro-vide practices to the market and to get an experiencedfeedback. We identify at least four challenging issuesthat can be effectively addressed here by the universityresearch institutes.

The professional competencies problem: IoT in-dustry will require an interdisciplinary education and aflexible stuffing. Students as the most driven and cre-ative workers, have to be involved in the developing.With big ambitions and wide skills, student society gen-erates most of the startups now. Therefore, IoT-enableduniversities are possibly the best place to produce devel-opers for the innovation industry.

The actual experience problem: This issue ad-dressed to distribute recent experience and best prac-tices inside the ecosystem. When new assets or servicesappear in the market, they should be tested and imple-mented to demonstrate best use cases and carry out im-provements.

The technology availability problem: This issuecan be specified because most of IoT cases are based onhardware and software. The technology availability as-sumes the open access to the developing facilities to en-able the cost and time effective prototyping. Solved bythe universities technology centres, it allows to performthe advanced technology delivering into the developer’ssociety, helps to accumulate best experiences, advancesthe methodological component of education. We wouldnote, that this approach is relevant and is being imple-mented more or less.

The fundamental research problem: This issue isbased on the market opportunities rather than pure func-tional value, because of all IT industry focused on thedemand generation. Therefore, the sufficient time andanalysis are required to summarize the actual market ex-periences and combine them with technology factors.

The challenge of bringing hundreds of teams ofhighly professional IoT developers for sustainable de-velopment is difficult to address. Universities turn outto be ideally located on IoT development crossroads, soboth industry and development team can leverage it tostart a number of small projects when a large number ofmultidisciplinary developers required.

To understand the variety of skills for the IoT de-velopment let’s consider a situation, where we analyzesensor data and control actuators by making decisionson the cloud platform. The most common educationalexample is the irrigational systems in the greenhouse[7, 8] or trash can in the Smart city [9]. First, devel-opers need to work with sensors on a physical layerthat require at least the hardware developer who will be

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able to solve the electrical connectivity problems andto register analog or digital information. Then theyneed to implement the system on chip (SoC) to ma-nipulate primary data and share them with other things.The next step requires understanding networking prin-ciples to connect multiple SoC into interconnected net-work [10]. IoT devices should communicate with eachother and with cloud platform through such protocolslike HTTP or MQTT [11]. This requires SoC softwaredeveloper familiar with programming in various opera-tional systems (primary on Linux and Microsoft Win-dows 10) [12] and programming languages (most usefulare: C/C++, Python, JavaScript, Java, Ruby).

Cloud technology is another significant piece ofknowledge for IoT projects. Developing on the cloudplatform is dealing with the target problem and defin-ing the system architecture. It requires a substantial ex-perience to use the appropriate cloud services to right-fully address project needs. That could be difficult evenfor skilled developers when they have to process a largeamount of data. Then the project should be supportedwith the web and mobile developer who is able to pro-vide data visualization. If the project needs the data ana-lyzing, it is necessary to have skills in statistics to imple-ment an analytical technology. Finally, the team shouldbe led by experienced and innovative thinking manager.

The natural solution we see here is to create a setof IoT templates which can be used by developers forfast prototyping. In a market with a great number ofIoT applications, the cloud services company will actu-ally face the problem of a technology distribution. Theskilled developer could take a role to implement tech-nology basics and to support the end user locally. Sucha set of concept solutions can be built in collaborationwith universities and have to cover most of IoT imple-mentations. We show one of such template in the nextsection.

3. IoT template solution

The R&D time for IoT projects is critical for survive.In many cases, the innovative project is able to win theon-premises system when it has the key advantage witha faster path to market. Thus it is significant to imple-ment the set of improved instruments for robust proto-typing and flexible services for developer needs [13].The best practice is to implement the prebuild ”starterkit” including cloud-based platform, web hosting re-sources, System-on-Chip (SoC) microcomputers withsimplified and reliable interfaces, common usable sen-sors and actuators. In this work, we describe such a kitbased on IBM Bluemix with pre-installed analytic ser-vices (IBM Watson IoT, Cloudant, dashDB, R-Studio,

and Node.js) and device IoT layer (RaspberryPi, Ar-duino, Grove sensors and wireless interfaces). The ad-vantages of this platform with examples we got duringthe student hackathon in Bauman Moscow State Tech-nical University are shown below. As a result, 36 hoursof intensive development and 150$ per kit was enoughfor every team to build working and very exciting IoTshowcase.

Since the cloud has become the primary platformto host IoT services [14], developers need to integratecloud-based resources into the project architecture. [15]shown the key technologies to implement an IoT solu-tion in agriculture and discovered the template which isbased on ZigBee networks. This approach may be ex-tended with analytical services and cloud-based infras-tructure as well. [16] attempted to categorize the ser-vices provided by the IoT in order to help applicationdevelopers build upon a base service. They outlined fourmain categories of IoT services and provided some use-ful examples: Identity-Related Services (i); InformationAggregation Services (ii); Collaborative-Aware Services(iii); Ubiquitous Services (iv). Based on this researchwe define here the ”starting kit” of services combinedwith solution network to attract the fast prototyping, andprovide the IoT template solution with appropriate me-thodical maintenance.

The target cloud platform has to be enabled for theInternet of Things: it should be scalable to be connectedwith many thing instances; flexible to implement newfeatures and services; and simple to reduce the devel-opment time. There is a list of candidates, such as Mi-crosoft Azure, Google Cloud platform, and others. Inthis work, we describe IBM Bluemix (Platform as a Ser-vice, PaaS) cloud to implement IoT template solution.

Bluemix is the cloud platform for the rapid proto-typing of various services and applications includingmobile and web kits, databases, programming environ-ments and SDK, data analytics tools, Internet of Thingsand cognitive computing infrastructure. It is based onopen source computer technologies like Cloud Foundryand Docker [17, 18]. To simplify the monitoring andcontrol functions, Bluemix provides the access throughthe dashboard and Cloud Foundry console [19]. Itshould be noticed that in many cases IBM provides easyaccess to faculties, students, and developers to Bluemix.

To support students with IoT concept, we developedthe basic cloud-based system for a wide area of imple-mentations. An illustration of the introduced concepts isdepicted in Figure 2. The system carries out the list offunctionality:

• Hosts at the bottom of hierarchy interact with mul-tiple physical objects. Through sensors and actua-tors, the IoT system registers current states of con-

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Figure 2. Internet of Things template solution

trollable things and able to change them.• SoC inside the host receives the primary data from

sensors for their further filtering and uploading. Itallows defining on this level the appropriate periodfor data uploading depending on the physical pro-cess speed.

• Multiple hosts can be distributed on a large areawith physical objects. To cover more area and im-prove functionality they could be interconnectedthrough another host into the chain [20].

• Data is sent to a hub or another host by thewireless interface like RF link, ZigBee, Bluetooth,WiFi, 6LoWPAN[21]. The appropriate interfacecan be defined by comparing such parameters asbitrates, encryption details, power consumption op-tions, signal coverage area and other features.

• The primary data are processing in a hub to formmessages for the cloud platform. This is usuallyunderstanding as packing data into the JSON objectand sending it to the message queue over TCP/IPstack. Hub is usually wirable connected to the In-ternet and represents multiple single hosts.

• The cloud platform receives data from multiplesources to store, analyze, and visualize them.

• Custom applications on the PaaS cloud are usingthe predefined cloud services to access stored data.For example, the application can receive HTTP re-

quest, parse and store it with the database service.Other application can get data from the databaseand generate the web page to visualize statisticswith graphs, charts, bevels, bars etc. The cloudapplication can send messages to the end user bySMS or push messaging.

• External data can be used by applications to im-prove analytic functions. For example, an appli-cation is able to predict KPI’s values on historicaldata.

• The IoT project can use HTML pages to visualizethings states and KPIs.

The template solution shown in Figure 2 can be ex-tended with more than 100 prebuild services from aBluemix catalog to support mobile development, ver-sion control, web applications, integration control, net-working, and APIs. In addition, Bluemix allows to builda new service from the Docker container and attach it tothe project through WebSockets or HTTP connections.This basic concept can be implemented in many areas tobuild IoT use cases. For example, it can be used to trackthe health data on a host device and move them throughthe mobile network or wifi to the cloud services. An-other way, for Smart homes this concept can be used asthe energy efficiency improvement, home security, andenvironment control. As for Smart Cities, it can im-prove the public infrastructure with traffic management,air and water quality monitoring or smart offices. Otherpowerful areas are agriculture and smart manufacturing.

4. Hackathon for IoT prototyping

A hackathon for the hardware and software develop-ment differs with that one just for programmers. It needsfrom organizers to be well equipped with embedded sys-tems both widely skilled in programming and cloud in-frastructure. To be successful, organizers should planthe preferred set of hardware and support teams with theappropriate environment. Unlike single programming,the hardware and software development needs individ-ual kits for every team (sensors, systems on a chip, wire-less interfaces, debug tools) and commonly used addi-tional tools (oscilloscopes, power supplies, digital ana-lyzers, soldering stations and other useful equipment).As our practice and Murphy’s law has shown, all of theadditional equipment was useful to get the best result.For that purpose, we used development resources fromthe Bauman MSTU Internet of Things laboratory.

Depending on the features, the price for additionalequipment starts from 1000$ and does not have any lim-its from above. Hopefully, we used generic parts withlow frequency and our additional expenses were near the1500$. As for the individual set, we spent about 2000$

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Figure 3. Internet of Things fast prototyping project’sarchitecture

per 14 teams, therefore 150$ is not so expensive for oneIoT showcase.

Let us get back to the concept. To be implementedin multiple instances, the concept solution infrastructurewas actualized into the educational project with a kit ofuseful and inexpensive environment [22]:• LEDs and buzzers were used as simple actuators.• More than a hundred of sensors was prepared for

projects development, but just the analog angle sen-sors and the digital temperature sensors were actu-ally used in the educational project. We preferablyused the simplified Grove interface to avoid shortcircuits.

• Arduino Uno microcomputers with Grove exten-sion board used to receive data from sensors.

• Wireless radio frequency modules RF 433MHzused to switch host with a hub.

• RaspberryPi microcomputer used as a computinghub and to control actuators. Through the RF linkand Ethernet, it can be connected to a host and tothe cloud side.

• IBM Bluemix implemented data storage, analyticalprocessing, and data visualization services.

The prototyping project’s architecture is shown inFigure 3. The project works as follows. Arduino regis-ters analog and digital data from sensors and sends themthrough the radio link. Such a link allows to data trans-mit from multiple hosts to the one or more computinghubs (RaspberryPi). The hub forms MQTT packets andtransmits them to the Bluemix cloud for storage and pro-cessing. Back to the hub, Bluemix sends control com-

mands to actuators.Let describe cloud part of the project in more de-

tails. MQTT packets are moving to the message bro-ker inside the Watson IoT service (also called IoT Foun-dation). It stores message queue and connection de-tails in the attached Cloudant database. The main ap-plication is based on Node.js framework and could bewritten with Node-Red visual editor inside the Bluemix.This tool is very friendly for beginners and positioned asone of the most useful Internet of Things online SDK.Node.js code primitives (nodes on Node-Red) are con-nected through multiple data streams into flows. Thefirst flow in our project receives the data stream fromIoT Foundation and stores it into the dashDB database.Another flow runs the predefined script in R languageto perform a regression analysis of stored data. This Rscript determines predictive values for some of the up-coming moments and sends them back to the dashDBand Node.js application.

According to the obtained primary data and analy-sis results, the application flow builds the web page withcharts and control buttons. A client can view charts ina browser and produce operations by clicking the con-trol button. After this, the application flow in Node-Redsends the MQTT command through the IoT Foundationservice back to the hub. This takes an action to theLED and buzzer attached with it. In the case when thepredictive value exceeds the limit, an application flowautomatically sends the MQTT command to switch thebuzzer on.

The project was divided into four stages:• Stage 1. Build and verify host with sensors• Stage 2. Build hub and receive data from the host• Stage 3. Make Bluemix template solutions and

build visualization on Node-Red• Stage 4. Make predictive analysis and send com-

mands back to actuatorsAs we noticed, this requires up to 6 hours to be build.

After that, all hackathon teams started to make their in-novative projects.

5. Projects description

Here is a short summary of some projects done bystudents during our hackathon. In the next section wewill describe one commercially successful project.

5.1 Smart crossroad

The crossroad control system analyses data frommultiple sources to focus appropriate attention on citi-zens movement. At first, it uses the cars traffic from theGIS portal (maps.yandex.ru) and people traffic from city

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events system (afisha.yandex.ru). Those data getting tothe Bluemix cloud to predict the citizens and cars trafficnear the crossroad. Next, the system sensing the aroundarea to understand citizen positions and light intensity.All this information used by Smart crossroad to under-stand how dangerous the crossroad is at the moment. Asa result, system controls smart backlights to make atten-tion to citizens for car drivers to make city crossroadsmore safety. In addition, video camera, attached to thesystem, captures vehicles near the stop line.

5.2 NRget(x)

This system allows distributing energy flows frommany sources to save energy for smart homes and smartcities. For that purpose, it analyses the data from ex-ternal sources and the information from solar batteries,wind generators, accumulators to control the stored en-ergy. System defines:• how much energy is produced from power genera-

tors?• what is the required power at the present moment?• how much energy was stored before?

This allows defining how much energy should be stored,sold or bought for effective energy consumption.

5.3 Smart Pill Box

This project is for those people who have difficultieswhile taking medicine. The problem is that many peopleoften miss the appointed time because of poor memory.People with disabilities such as bad eyesight sometimesmix pills up. The team created a smart pill box whichannounces users when they should take their medicineand lights up the required compartment. The hardwareconsists of the pill box with sensors, LEDs, and buttons,while the software is based on the Bluemix cloud ser-vices and Android application.

5.4 RealClimate

This project designed to capture and replicate vari-ous climate conditions. The idea is to create the climateconditions in real time and equal to that one in anotherplace. The project consists of 3 different modules. Thefirst module is meant to be placed in natural conditions,collect data about the surrounding climate (temperature,humidity, soil moisture, etc.), and upload the collecteddata to the Bluemix. The second module is placed inthe area, where the desired climate is to be replicated.It collects information about the second climate and up-loads it to the cloud. The third module is connected tovarious systems for recreating climate conditions (AC,irrigation, humidifier, etc.).

Information in the cloud from the two climate zonesis compared, and commands are sent to the third moduleto enable/disable the necessary subsystems. This projecthas many potential use cases, four of which are listedbelow:

• Zoos and arboretums: with the help of this prod-uct, stress associated with transporting plants andanimals can be reduced to a minimum. The op-posite effect can also be used for creating naturalstress, which strengthens the immune system andincreases vitality. This can be achieved by monitor-ing and recreating climate conditions in real-time.

• Industrial use: in farms and greenhouses for in-creasing crop yield.

• Virtual reality systems: for creating a more immer-sive experience.

• Science: for tracking and analyzing climatechanges on planet Earth (and other planets in thefuture). This can also help forecast climate anoma-lies.

5.5 Smart Escalator

The target of the Smart Escalator project is to dis-tribute traffic flow between underground escalators ac-cording to accident prevention rules. Expected trafficflow calculation is based on readings of sensors builtin turnstiles and also on analyzed statistics. Statisticaldata is being collected during previous several weeks sothere’s ability to predict future traffic flow in the certainhour of the certain day (traffic difference between week-days and holidays is also considered).

Parsing of Internet resources allows to precise pre-diction according to the future or current events nearcertain subway station (e.g. public events like sportsmatches, nearby stations stoppage and so on). The smartsystem makes a decision to turn off and on escalatorsand reversing their direction. When they are stopped orreversed the system informs passengers with indicators,closes the entrance to the escalator and completes onefull turning cycle of stairs. Then the system closes theescalator and performs operations for stopping or chang-ing direction. With this feature, the project increases thesafety and convenience level of subway transportation.

5.6 M&F

This project is to identify people by using IBM Wat-son visual recognition service. The problem is to findthe moment when face position is most useful for cap-turing and recognition. For this purpose, the ultrasonicrange finder detects an object at a correct distance fromthe camera. Therefore it does not allow to capture therandom objects outside the recognition zone. After cap-

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Figure 4. Smart refrigerator project

turing, the picture is transmitting to the Bluemix for fur-ther recognition. Thus, the image is comparing with pre-defined faces on Watson service. If the person is suc-cessfully identified, Node.js application sending MQTTmessage to the actuator (lock subsystem, alarm etc.).This project results can be used for security in Smartcities, Smart homes and Smart offices.

6. Example of commercial project

The commercial success of the Internet of Thingsproject is the result of the effective solution with a small

cost. Such a project was immediately demanded by thebusiness after the hackathon. The Smart refrigerator sys-tem aimed to upgrade refrigerators with functions to getinformation about products being stored and to send datato the cloud analyzing the system. This cost-effectivesystem is based on Arduino, RaspberryPi, and Bluemixto define the amount of stored food on every refrigera-tor’s shelf. If the weight is lower than normal limit, thesystem automatically sends an order to the online store.In addition, the system monitors food terms and sendsalerts to the LCD and web panels (for example, whenfood was stored on the shelf for a long time).

Inside the refrigerator, the weight sensor, tempera-ture and humidity sensors are used to define store con-ditions. All the data sent by the Arduino are followingto the RaspberryPi computing hub. This device visual-izes the food weight and store conditions for local userand sends it to the cloud. IBM Bluemix is used to ana-lyze and visualize data from multiple shelves and refrig-erators. Node.js application stores data in the dashDBdatabase makes orders for food restocking and visualizeanalysis results.

This idea of a refrigerator which able to sense thekind of products is not new [23]. But the existing smartrefrigerators are expensive and require additional sup-port. As a result, this project got the attention from thefood market companies. The brewer company thinkingabout how to control the beer supplies on the refrigera-tors shelves in city stores. Existing equipment does notallow to determine the storage conditions and inventory.Therefore, it is necessary to develop a system to get in-formation from many refrigerators around the city andanalyze it to schedule automatic delivery. The companycan ask merchandiser in every store to distribute beerinventories on the shelves or refrigerators (Figure 4) ifneeded. The system automatically checks the storageconditions and sends information to the beer companyand to the merchandiser. If those conditions are violated,this automatically raises the request to support service.The brewer company aims to analyze data to create thebest conditions for sales. Smart refrigerator system canhelp company to understand:

• how many beer bottles sold in different stores.• how to distribute bottles on the refrigerator shelves

in the best way.• how many beer bottles should be delivered to the

store?• the beer storage conditions.

7. Conclusion

We introduced the fast prototyping technique for theInternet of Things projects to make them competitive

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enough to be already acquired by business. The shownIoT template solution is based on inexpensive compo-nents and the IBM Bluemix cloud platform. The con-cept was implemented as the educational project to behelpful piloted at the IoT hackathon in Bauman MoscowState Technical University. We shown some innovativeprojects developed by the hackathon teams.

Smart refrigerator project allows retail companies toanalyze information about the products in city stores.The brewer company used this project to create an ana-lytical system for schedule automatic delivery and checkstorage conditions.

More detailed framework to address fully industryneed is yet to be developed and it could be a good areafor further research. We also plan to create a network ofIoT labs in technical universities in close collaborationwith industry. It can extend both the set of IoT templatesolutions and perspective showcases.

8. References

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