Knowledge Design in the Internet of Things: Blockchain and Connected

Refrigerator

Samuel Szoniecky and Amri Toumia

Paragraphe Laboratory, University Paris VIII, 2 Rue de la Libert

e, 93526 Saint-Denis, France

Keywords:

Blockchain, Internet of Things, Power to Act, Modeling, Knowledge.

Abstract:

The Internet of Things takes place in our daily life, but many users do not understand their relationships and

interactions with these objects. We assume that dynamic and interactive representations of the power of action

of users and objects are means to better understand what these devices are capable of. To do this, we design

a secure and privacy-conscious design of knowledge in the connected object environment. We will analyze

the example of a connected refrigerator to understand how to use the Blockchain to develop Digital Social

Innovations.

1 INTRODUCTION

The Internet of Things (IoT) is witnessing a fast

growth for few years now. A study done by the IDC

consulting ﬁrm estimates that, by 2022, investments

on the IoT sector should reach 1.200 billion dollars

by 2022

Economists consider these technologies as a new

”growth driver” as long as the constraints that are pre-

venting users from taking part in the IoT are solved. A

French study done by Promotelec

reveals that these

constraints are due to users’ lack of trust in these tech-

nologies. Users wonder if they are harmful for the

health and dangerous to vulnerable individuals (chil-

dren, elderly people)and if they preserve the conﬁden-

tiality of the collected data.

Beyond this desire to preserve the familiar space,

interviewed users also question the simplicity of use,

cost and usefulness. This last point is particularly im-

portant to us because the question of the usefulness of

a digital device is undoubtedly the ﬁrst question that

should be asked because it places the individuals in a

reﬂexive approach in relation to their own practices:

do I need this product? This attitude of questioning

is with no doubt the guarantee of a reasonable use of

technologies (L

evy, 2017) (Citton, 2014) which coun-

https://start.lesechos.fr/actu-entreprises/technologie-

digital/comprendre-l-internet-des-objets-iot-en-5-questions

-12253.php

https://www.promotelec.com/wp-content/uploads/

2018/06/Etude-Objets-connect%C3%A9s-pour-lhabitat-

PROMOTELEC-21-juin.-pptx.pdf

terbalances the fashion effects or the consumerist ten-

dencies of our societies. But, how to evaluate the use-

fulness of a device like a connected refrigerator?

Manufacturers of connected refrigerators adver-

tise devices capable of automatically recognizing

food expiry date, reordering missing groceries and

evaluating food compositions and their impact on

consumers’ health. However, the usefulness of these

features is not obvious to all users. For example, au-

tomatically ordering food depends on the balance of

the user’s account or on the blood tests of the peo-

ple in the household which conditions favoring one

food over another. To be really useful, the refrigerator

should continuously be aware of the users ﬁnancial

and serological state in order to adapt in real time to

the changes of situations. Will we consent to give this

information to a machine? How can we control the

sharing of this information? Which responsibilities

are we willing to give to algorithms?

The answers to these questions are not unique be-

cause each person can answer them differently and

because the answers can vary depending on contexts.

So, to answer the question of the usefulness of a con-

nected refrigerator or any other smart object, we need

to ﬁnd ways to handle the different questions that arise

from their use and their various possible answers, all

this while ensuring the security of collected data and

user privacy. Moreover, it is necessary that this data

is interoperable and above all intelligible so that the

experience of some beneﬁts to the understanding of

others.

From this perspective, it becomes fundamental to

Szoniecky, S. and Toumia, A.

Knowledge Design in the Internet of Things: Blockchain and Connected Refrigerator.

DOI: 10.5220/0007751703990407

In Proceedings of the 4th International Conference on Internet of Things, Big Data and Security (IoTBDS 2019), pages 399-407

ISBN: 978-989-758-369-8

399

design knowledge management processes to measure

interactions between humans and connected objects

in order to evaluate the relationships between these

two types of actors. The objective is to provide clear

information about what these actors can do and for

which purposes. To do this, we can model the power

of action of these actors (Brun, 2017) to analyze how

their interactions in a given situation and for a spe-

ciﬁc purpose, increases or decreases their power to

act. Our hypothesis is that dynamic and interactive

representations of this power to act are a way to bet-

ter understand the capabilities of IoT devices: what

are the offered services? Which difﬁculties can be

encountered? What are the relationships between dif-

ferent objects? The main issue then becomes a ques-

tion of knowledge design: how to manage the inter-

actions between the knowledge of users and those of

connected objects in a digital environment?

Alongside these knowledge management issues,

the centralized architecture of IoT platforms raises

many issues in terms of security and privacy pro-

tection. Due to its decentralized and distributed na-

ture, Blockchain technology seems to address these

issues (De Filippi, 2018). However, the character-

istics of the IoT devices, for example their limited

computing power, do not facilitate this adaptation.

Similarly,understanding the complex mechanisms in-

volved in the Blockchain makes this technology difﬁ-

cult to master for non-specialist users.

To illustrate and clarify how to conceive a secured

knowledge design that respects users’ privacy in the

context of smart devices, we will begin by examining

the Blockchain and its related technologies. In partic-

ular, we will focus on ”smart contracts” which give

us a glimpse on a new way of contracting without a

need for a trusted third party. In a second step, we

will describe how to use the Blockchain in the IoT

through the example of a dynamic and interactive de-

vice for collectively analyzing activities related to a

connected refrigerator. Finally, we will discuss the

advantages and drawbacks of this type of system.

2 WHAT IS THE Blockchain

In 2008, Satoshi Nakamoto (pseudonym) published

a paper on Bitcoin (Nakamoto, 2008). In this arti-

cle, the author describes a new cryptocurrency called

Bitcoin. The latter is based on a technology called

Blockchain. It is a public distributed and decentral-

ized ledger in which transactions are recorded across

multiple nodes of a peer-to-peer (P2P) network. The

Blockchain is attack resistant, ubiquitous, veriﬁable

and auditable.

To transfer virtual currency, Blockchain users,

who are identiﬁed by their public keys,generate and

broadcast transactions on the network. These transac-

tions are grouped into blocks by users. When a block

is ﬁlled, it is added to the Blockchain after a ”mining”

process. To mine a block, nodes of the network, called

”miners”, try to solve a cryptographic puzzle called

”Proof-of-Work” (PoW). Once the block is validated,

it is time stamped and added to the Blockchain. The

transaction is then visible to the receiver as well as to

the entire network (Saleh et al., 2018).

Since the invention of Bitcoin, other consensus

mechanisms beside PoW have emerged. For exam-

ple, we can talk about Proof-of-Stake (PoS) or Proof-

of-Importance (PoI). In the ﬁrst one, users who have

more coins have the responsibility of validating trans-

actions and protecting the system because they are

the ones who invested the most in it and are there-

fore the most concerned about its good performance.

Proof-of-Importance was introduced by NEM (Cap-

stone, 2015). In this consensus mechanism, a rep-

utation system is built for the network, based on an

importance value associated with each account. The

higher this value is, the greater the chance of being

chosen to create the next block.

Based on the work of (Febin, 2018) (Sher-

min, 2017), we can distinguish three main types of

Blockchain :

• Public Blockchain: as its name suggests, it is a

large public ledger. No entity is in charge and

all nodes of the network can read data from the

Blockchain, participate in transaction validations

and auditing. Having a computer with an inter-

net connection in enough to become a node of

the network and get a complete history of the

Blockchain. The advantages of this system are

transparency and anonymity, since each node is

only identiﬁed by its public key. In addition, the

redundancy of the public Blockchain and its repli-

cation over the network makes it very secure and

immutable. However, transaction validations are

slow and require signiﬁcant computation power.

This type of Blockchain is mainly used for cryp-

tocurrencies such as Bitcoin or Ethereum.

• Private Blockchain: It is a kind of restricted

Blockchain. It is under the management of an

authority that oversees the creation, veriﬁcation

and validation of each transaction. The data is

not open to the public and permissions are re-

quired to access it. Because of their nature, pri-

vate Blockchains do not provide decentralized se-

curity, but offer increased efﬁciency for checking

and validating transactions. Their use is destined

for public or private companies.

IoTBDS 2019 - 4th International Conference on Internet of Things, Big Data and Security

400

• Consortium Blockchain or Public Blockchain

with permission: It is a hybrid between public

and private Blockchains. It operates under the

supervision of a set of predetermined nodes that

are allowed to verify and validate blocks or trans-

actions. On the other hand, the data may be open

to the public or restricted in the case of sensitive

information. It is up to the nodes to choose this in

advance. R3

and Energy Web Foundation

are

examples of this type of Blockchain.

Given that the source code of Bitcoin is open

source, many forks were possible and many new ver-

sions of peer-to-peer cryptocurrencies have emerged.

However, the underlying protocol of Bitcoin, specif-

ically the Blockchain technology, has attracted many

new ideas. Researchers have been thinking of ways to

use this decentralized distributed ledger for purposes

other than virtual currencies. Thus, Blockchain got

involved in any type of transaction or agreement be-

tween parties that previously required a trusted third

party to regulate it.

In this context, Blockchain platforms, such as the

Ethereum

, allow developers to create and execute

”smart contracts” within the Blockchain architecture.

The term ”smart contract” was introduced for the

ﬁrst time in 1994 by Nick Szabo (Szabo, 1994) as ”

computerized transaction protocols that executes the

terms of a contract ” . He gave the example of a vend-

ing machine through which a user could enter data or

value and, in return, receive an item from that ma-

chine. While enforcing a standard contract is usu-

ally insured through laws and a trusted third party

that guarantees its implementation (the State for ex-

ample), enforcing and implementing a smart contract

is done by an algorithm that is encrypted and added to

the Blockchain. This smart contract can be automati-

cally applied or executed taking into account a set of

predeﬁned conditions.

According to Gavin Wood (Wood, 2016) , co-

founder of Ethereum, smart contracts have the follow-

ing characteristics:

• Atomicity: the entire code of the contract must be

executed or nothing is executed.

• Synchrony: operations cannot interfere with each

other.

• Provenance: all messages can be inspected to de-

termine the caller’s address.

• Permanence: the data of a contract are permanent.

https://www.r3.com/

http://energyweb.org/

https://www.ethereum.org/

• Immortality: a contract cannot be removed from

the outside

• Immutability: the smart contract code cannot be

changed.

Ethereum, introduced by Vatalik Buterin in 2013,

is an example of a Blockchain platform speciﬁ-

cally designed for the creation and application of

smart contracts. Like Bitcoin, Ethereum is a pub-

lic Blockchain network. While Bitcoin is designed

for use cases involving transfer of virtual currency,

Ethereum allows developers to create and deploy

other decentralized applications based on Blockchain

technology (Buterin, 2014). In Ethereum, miners

work for a currency called Ether. That is what incen-

tivize developers to write quality applications and en-

sure that the network works effectively. Thus, Ether,

in addition to being an exchangeable cryptocurrency,

is like the fuel that allows decentralized applications

to run.

Contracts in Ethereum should not be seen

as something that should be ”fulﬁlled” or

”complied with”; rather, they are more like

”autonomous agents” that live inside the

Ethereum execution environment, always exe-

cuting a speciﬁc piece of code when ”poked”

by a message or transaction, and having di-

rect control over their own ether balance and

their own key/value store to keep track of per-

sistent variables. (Tsui, 2016)

Thus, from this deﬁnition we can understand that

smart contracts are executed, as designed by their de-

velopers, when certain conditions are met, and with-

out any human intervention. They are powered by the

Ethereum Virtual Machine (EVM) and Ether.

According to Ethereum’s yellow paper (Wood,

2015) , the EVM is a quasi-complete Turing machine.

Indeed, a Turing machine normally has inﬁnite re-

sources, while the EVM’s resources are deliberately

limited. The qualiﬁcation of ”quasi-complete” comes

from the fact that the calculation is intrinsically linked

to an amount of Ether allocated at the time of creation

of a transaction, which limits the total amount of cal-

culation that can be performed. This can be consid-

ered as equivalent to a fee. On the Ethereum network,

each transaction requires the payment of an execution

fee. To be able to program smart contracts, devel-

opers rely on ”Solidity”, the Ethereum programming

language that is similar to Javascript.

Knowledge Design in the Internet of Things: Blockchain and Connected Refrigerator

401

3 THE Blockchain IN THE IoT

The Internet of Things, or IoT, is a system of inter-

connected devices, sensors and digital machines that

can communicate and share data over a network with-

out the need for human intervention(Saleh, 2017).

According to Gartner (Pettey, 2015), the number of

smart devices connected to the Internet is expected to

reach about 25 billion by 2020, generating an eco-

nomic proﬁt of 200 billion dollars.

Because of the generation of massive amounts of

personal data, the IoT is facing issues such as the ad-

ministration of these smart objects, safety and trace-

ability , but also privacy protection and data access

management...

Due to its distributed nature, its consensus mech-

anisms that reconcile divergent interests, and its dis-

tributed trust process that does not require third par-

ties, the Blockchain can provide answers to these is-

sues.

In their article (Atlam et al., 2018), Atlam et al.

defend the idea that the shift of the IoT architec-

ture toward a decentralized system could be a way

to solve many problems, especially in terms of secu-

rity. In addition, Brody et al. (Brody and Pureswaran,

2014) argue that in order to be proﬁtable and sus-

tainable, the ever-growing ecosystem of IoT devices

should evolve into a decentralized architecture, reduc-

ing maintenance costs for manufacturers and increas-

ing user trust in those products.

However, as mentioned by Dorri et al. (Dorri

et al., 2016) , adapting Blockchain mechanisms to the

IoT is not straightforward. In fact, the mining process

requires a lot of computing power that IoT devices

do not have. Moreover, it is a relatively slow pro-

cess, while IoT applications require low latency. In

addition, the Blockchain has scale-up problems and

performance decreases as the number of nodes on the

network increases, which may be problematic for IoT

networks that involve a large number of devices inter-

acting with one another. Finally, the underlying pro-

tocols of the Blockchain generate signiﬁcant indirect

trafﬁc which may be undesirable for some IoT devices

with limited bandwidth.

In this context, a lot of research is being done on

how to use and adapt the Blockchain to the IoT envi-

ronment. For example, we can cite Mettler (Mettler,

2016), who applied Blockchain in healthcare envi-

ronment, whether for public health management, for

medical research based on the personal information

of patients or for quality insurance in medicine man-

ufacturing. Dorri et al. (Dorri et al., 2017) presented

an adaptation of the Blockchain to the case of smart

homes. In their article, they show that it is possible to

reduce the load on the network while ensuring data

security and protection of users’ privacy by group-

ing devices in clusters and using local Blockchain. In

addition, Christidis et al. (Christidis and Devetsiki-

otis, 2016) demonstrated the beneﬁts of Blockchain

and smart contracts for sharing services or resources,

as well as for task automation and veriﬁcation. In

(Huh et al., 2017) , Huh et al. showed a method to

manage IoT devices using Ethereum. Using smart

contracts and Ethereum accounts, an electricity me-

ter was continuously sending electricity consumption

to a smartphone, which in turn was sending instruc-

tions to a light bulb and an air conditioner to update

their energy consumption modes. Finally, the authors

of (

Ozyılmaz and Yurdakul, 2017) proposed a con-

cept to facilitate Blockchain use for resource-limited

IoT devices.

4 KNOWLEDGE DESIGN

SYSTEM FOR A CONNECTED

REFRIGERATOR

To understand and analyze the use of the Blockchain

in the IoT, let us study the use of a connected refrig-

erator in a family of three people. To conduct this

study, we use an activity modeling method based on

an ecosystem approach that sees activity as a cor-

relation between existence modeling (ontology) and

knowledge experimentation (ethology). We adopt a

global and evolving vision to analyze information-

communication issues through the analogy of ecosys-

tems in order to take advantage of an approach that in-

cludes the complexity of life in a ﬁeld often analyzed

with ﬁxed models derived from engineering sciences.

Following this analogical grid, we consider that the

analysis of the activity goes through a double model-

ing, that of the existences which populate the ecosys-

tems and that of the cognitive experiments that these

existences maintain with each other.

To facilitate the modeling and make it accessible

to as many people as possible, we propose to do this

work using a graphic vocabulary that brings into play

an analogy that is both simple and complex to give the

user the means to invest already acquired knowledge

and thus more easily understand the functioning of the

device. The desktop analogy used by computer oper-

ating systems is a good example of a graphical vocab-

ulary. However, in the case of the IoT, it is unsuitable

for a context that we call an ecosystem (Roxin and

Bouchereau, 2017). That is, an environment where

a multitude of human and algorithmic actors evolve

continuously in what they are, what they know and

IoTBDS 2019 - 4th International Conference on Internet of Things, Big Data and Security

402

the relationships they have with each other.

Let us take the example of a connected refrigera-

tor that has an automatic food inventory management

feature which meets the needs and desires of fam-

ily members. To implement this functionality with a

desktop analogy, users should be asked to ﬁll in ”lists”

corresponding to their needs and desires, in ”folders”

through ”forms” that will be sent to food suppliers

and other companies that can access this data. In this

case, the interactions with the refrigerator are similar

to those of an ”accountant” and the story that the users

co-construct with the connected object becomes only

”administrative”. Now, imagine the same refrigerator

with the same functionality, but this time by setting up

the analogy of the garden. In this case, the user is no

longer facing lists, but gardening ”plants” that grow

and play with ”animals” that interact with them. The

user becomes a ”gardener” and ”cultivates” a living

story with the digital environment to make a knowl-

edge ecosystem their own.

4.1 Principles of Modeling Knowledge

Ecosystems

The basic principles of modeling knowledge ecosys-

tems (Szoniecky and Saﬁn, 2017) are based on the de-

scription of the existences that compose them. They

are deﬁned by four distinct existential dimensions:

physical, concept, actor, relation. These dimensions

give the modeler an analytical grid to organize the

chaos of ecosystems by distinguishing elements each

possessing their own kind of knowledge accessible

according to a dedicated metric:

• physical dimension = Euclidean metric ⇒ knowl-

edge of shocks

• concept dimension = topological metric ⇒ exper-

imentations of intuitions

• actor dimension = topographic metric ⇒ social

knowledge

• relation dimension = temporal metric ⇒ prag-

matic knowledge.

The diagram in ﬁgure 1 illustrates the organization

of modeling by enriching it with a double translation.

First, to each dimension is associated a pretopological

element useful to formalize the informational trans-

formations of the ecosystem:

• physical = outside,

• concept = interior,

• actor = edge,

• relation = stream.

Second, the dimensions of existence are translated

according to the analogy of a plant:

• physical = branch,

• concept = root,

• actor = seed,

• relation = sap.

It is from this analog translation that we propose

a dynamic and interactive representation of the power

to act in the form of a semantic mapping that we de-

ﬁne as dynamic and interactive interfaces composed

of:

• a conceptual coordinate system to formalize an in-

teroperable expression

• a projection of concepts in a graphic vocabulary

to visualize expressions

• devices for interacting with the user (click, drag &

drop, gesture capture, etc.) to manipulate expres-

sions

This cartography takes as graphic vocabularies

those of geographical cartography, housing plans or

any other graphic forms like stars, icons, drawings,

diagrams, etc. What matters is the ability of the map-

ping to make explicit the interactions of the users with

the graphical vocabulary and the projection of these

interactions in four coordinate systems:

• material spaces

• conceptual spaces

• networks of actors

• temporalities.

Passing through these coordinate systems allows to

formalize the expression making it interoperable with

other expressions. Thus the interpretation goes

through the positioning of the user in these four co-

ordinate systems. Positions that can be automatically

calculated for example in the material space thanks to

the GPS or in temporality thanks to the synchroniza-

tion of the world clocks. On the other hand, positions

in the network of actors and in the conceptual spaces

require interactions with the user.

4.2 Modeling the Ecosystem of a

Connected Refrigerator

To illustrate the use of this modeling method in the

ﬁeld of the IoT, here is the modeling of activities re-

lated to the use of a connected refrigerator. This dia-

gram in ﬁgure 2 shows how Blockchain technologies

are used to manage three types of activity. The ﬁrst is

a ”transfer of assets” corresponding to the purchase of

Knowledge Design in the Internet of Things: Blockchain and Connected Refrigerator

403

Figure 1: Modeling of existential dimensions in a knowledge ecosystem.

the refrigerator by a transaction between the ”manu-

facturer”, the ”distributor” and the ”family” who buys

the product. This ﬁrst act formalized by a ”bill” ini-

tializes the chain and creates the second block in the

form of a ”smart contract” specifying the ”guaran-

tees” and their automatic application in case of ”main-

tenance”. This chain is replicated for these three ac-

tors which ensures its durability and immutability.

The rest of the chain is composed of a register of in-

teractions that each member of the family will operate

with the refrigerator.

In this modeling, the interactions consist of eval-

uating the use of the refrigerator from semantic maps

that feed a chain dedicated to the refrigerator that will

have its own blockchain identiﬁed by the product ref-

erence (serial number). Activity data may also in-

clude the assessment of foods that are stored in the

refrigerator. In this case, the data will be formalized

in a blockchain corresponding to a food (barcode) and

could enrich with new blocks a Blockchain dedicated

to food traceability (for example a farm chicken).

The IoT ecosystem of the connected refrigerator

thus consists of a multitude of blockchain each de-

voted to a particular product. Whatever the case, the

blockchain ensures the security and durability of in-

formation through the protocol it uses. However, it is

necessary to deﬁne who is authorized to consult this

information. In the example we have modeled, should

we make all blocks of the chain public? It is proba-

bly useful to analyze the blockchain to know what the

children eat, how often and what they think. But is

this information in the public domain freely available

to all or only available to parents or companies willing

to pay?

To answer these questions, we use the diagram

above to specify whether relationships (color lines)

between actors (hexagrams), documents (rectangles)

and concepts (ovals) are open or closed and under

which conditions. These relationships represent the

”boundaries of trust” of the ecosystem, they deﬁne

the rights of circulation of information. They can

be formalized by ”smart contracts” which will con-

stitute a meta-blockchain used to manage the multi-

ple Blockchains of the IoT ecosystem. At this meta

level, users will deﬁne communication strategies at

their household level. These will serve as a basis for

discussing ecosystem development strategies at larger

scale levels: cities, regions, nations, world.

4.3 Using the Blockchain in the

Ecosystem of a Smart Refrigerator

Based on the previous diagram, we will analyze the

possibilities of using the Blockchain in the context

of the Internet of Things, speciﬁcally for the ecosys-

tem of connected refrigerators. Let us start with the

smart refrigerator manufacturer. The data on the prod-

uct components and the place of manufacture could

be stored on a public permissioned Blockchain that

would be controlled by the manufacturer of the con-

nected refrigerator. This Blockchain can also store

data on the product’s ﬁrmware, and updates could be

done via the Blockchain, which would allow for bet-

ter availability and traceability of these updates. War-

ranty data can also be stored in this Blockchain.

Blockchain can also be used in food monitoring

and traceability systems. Indeed, traceability is cru-

cial in the food supply chain to ensure food security

for consumers. Blockchain technology allows you

to save and share information about food products at

each stage of production, throughout processing and

distribution. This technology represents an opportu-

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404

Figure 2: Ecosystem of the Blockchain for a connected refrigerator.

nity for the actors of the production chain, because it

allows them to control more easily the supplies and

the potential returns while providing quality informa-

tion to the ﬁnal consumer. It is also a way to avoid

food scandals and ensure a rigorous transfer of re-

sponsibilities.

For end-users, the connected refrigerator is sup-

posed to automate tasks such as purchasing and track-

ing products. To do this, it must store this infor-

mation in a database. In addition, the connected re-

frigerator can generate recipes based on the prefer-

ences and health of the user. Management of access

to all this stored information could be managed via the

Blockchain, where each access to the data is recorded.

Thus, users will not have to worry about their data and

who has access to it. Moreover, the purchase process

could be easily integrated into a blockchain network

where cryptocurrency is exchanged providing an ap-

propriate billing layer.

Finally, connected refrigerators could be used in

businesses or school restaurants and blockchain could

facilitate sharing (controlling access to a refrigerator,

voting on menus and shopping lists ...)

5 DISCUSSION

Blockchain technology has revolutionized the relia-

bility of information in a distributed and decentral-

ized network. We believe this can be a way to build

trust in distributed environments without the need for

a trusted third-party. In addition, a system that guar-

antees data reliability would help secure and facili-

tate information sharing. Adapted to the speciﬁcities

of the IoT environment, the Blockchain could solve

some of the current issues of the Internet of Things.

The Blockchain can also be used to implement

access control mechanisms through smart contracts,

eliminating the need for a trusted third party while

having an immutable log of all data access.

This technology could help transform the current

architecture of IoT systems into a decentralized orga-

nization, reducing maintenance costs while ensuring

security and reliability.

Research on the use of the Blockchain in an IoT

environment is still in its infancy. Some problems per-

sist and hinder this integration. Among them, we can

talk about privacy protection issues. Since the details

of all public keys are visible on the network, the risk

of private information disclosure via data crossings

is not insigniﬁcant. Indeed, cryptocurrency wallets,

for example, have their public key displayed in plain

view, particularly, in the block that recorded the trans-

action that transfered money to it. In addition, the

Blockchain presents some scalability issues because

the time to add a block increases with the number of

nodes in the network.

In addition, the Blockchain does not comply with

the GDPR. For example, the GDPR requires that

data do not leave the EU, unless to jurisdictions with

equivalent controls, which can be problematic in a de-

Knowledge Design in the Internet of Things: Blockchain and Connected Refrigerator

405

centralized global network. Similarly, the question

of the ”right to be forgotten” is not implemented in

the Blockchain because it is immutable by nature and

therefore, the data stored there cannot be erased.

The convergence between Blockchain technology

and the emergence of collective intelligence projects

is in line with our proposals of knowledge design in

the IoT. They develop in the context of Digital Social

Innovations (DSI) that can be described as:

”First, at the social level, the DSIs cover

perimeters of collective use, involving a mul-

titude of actors in order to co-create a soci-

etal value [...]. Secondly, at the technological

level, they generate an open operating process

based on an innovative hardware and soft-

ware architecture as well as on speciﬁc func-

tional mechanisms. Finally, at the ecologi-

cal level, the DSIs focus on responsible inno-

vation [...] and the desire to respond to so-

cial and environmental problems, improve the

quality of life of citizens and create a sense

of social justice” (Boulesnane and Bouzidi,

2018).

In the case of the IoT, DSIs aim to develop a multi-

agent architecture for ambient intelligence based on

environmental modeling through representations of

knowledge such as EKRL (Environment Knowledge

Representation Language) (Dourlens, 2012). De-

signing these architectures with blockchain technolo-

gies would keep the history of interactions between

agents and with users to build a representation of dis-

tributable and non-falsiﬁable knowledge. In addition,

the blockchain would make it possible to contractual-

ize certain actions such as purchase requests or access

authorizations to private data and thus better manage

the proliferation of this data in digital networks.

6 CONCLUSION AND FUTURE

WORK

In this article, we looked at the Blockchain and re-

lated technologies. We have seen that it has charac-

teristics that could beneﬁt the Internet of Things. We

used the example of a connected refrigerator to illus-

trate, with an example, the possible applications of the

Blockchain. The integration of the Blockchain into

the IoT ecosystem can provide solutions to some cur-

rent issues.

However, there is still work to be done to recon-

cile an IoT environment with limited resources, with

the requirements of Blockchain technology. Mainly,

we plan to build a prototype to test the feasibility of

an information and communication device using the

blockchain in an IoT ecosystem, then, design an eval-

uation protocol for this device to analyze how the de-

vice increases or decreases the power to act of users

in their interaction with the connected refrigerator. Fi-

nally, we want to test the prototype and the protocol

in a real environment.

We have shown how a knowledge gardening de-

vice makes management of these ecosystems acces-

sible and how Blockchain technologies ensure both

security and sustainability of information. The com-

bination of these two approaches gives the users of

connected objects the means to deﬁne ”boundaries

of trust” and to think about strategies for developing

ecosystems. This research reveals many issues such

as those related to the ergonomics of augmented re-

ality devices for gardening knowledge, or that of the

efﬁciency of Blockchain technologies, particularly in

terms of computing resources and availability of dig-

ital networks. It is probably illusory to think that

these technologies can be conceived in all contexts.

It will therefore be necessary to precisely deﬁne the

resources needed to consider the conditions for the

development of such a device. More generally, the

collective intelligence platform that we are consid-

ering poses many technical, legal, political and eth-

ical questions (Floridi, 2018) (Russo, 2018) that will

have to explore in a concrete framework of experi-

ments such as those of those of the Human At Home

project

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