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Authors: Sofia Terzi (, Konstantinos Votis (

Abstract—The adoption of Information Communication Technologies (ICT) and Web 3.0 have the potential to impact in the e-government sector by transforming the way public administrations provide advanced and innovative services but also the way citizens interact with them. In this direction, Blockchain and Artificial Intelligence (AI) are nowadays among the most disruptive technologies and will fundamentally reshape how we live, work, and interact with the government sector and industries as well, due to the unique features they bring. In this paper we present how Blockchain 3.0 and Artificial Intelligence can enhance the available means for robust, secure, scalable and authenticity provenance solutions. Consequently, two validation scenarios are analyzed in order to present how the blockchain smart contracts and AI agents can be used practically to support energy and health oriented e-government services.

Keywords-blockchain 3.0; smart contracts; e-government 3.0; artificial intelligence; energy; e-health; IoT; web 3.0;

I.          Introduction

Blockchain (BC) technology has been nowadays characterized as a critical and important disruptive technology for many industries and applications. Starting with Bitcoin [7] which is a finance oriented extremely ingenious distributed shared ledger and peer-to-peer value transfer technology, BC established trust between unknown stakeholders and automation of payments. Bitcoin reformed the finance and supply chain industry by shortening the time needed to complete time-consuming processes as well as removed almost all intermediaries.

This kind of blockchain technology for financial payments automation without intermediaries is known as Blockchain 1.0. The technology acknowledged as Blockchain 2.0 followed with the Ethereum project [8], which differed from BC 1.0 because of its support to smart contracts (SC) usage. Other BC 2.0 technology projects followed, such as Hyperledger’s HL Fabric, Sawtooth, Iroha [9] and R3’s Corda [10] to name a few. Smart Contracts (SC) are computer programs written and run on the blockchain to provide security and automation to the system, making it possible for participating parties to agree upon certain conditions and according actions to be performed when these conditions are met. These features of SCs reshaped even more the supply chain processes by enabling additional on-chain actions as assets tracking, and in parallel, equipped BCs with the necessary characteristics to be used in other business cases, apart from the supply chain. Actually, BC is now used in many industries such as healthcare [1][2], education [3], government [4], charities [5], real estate [6], insurance [16] and banking [15]. This expanded field of applications supported by BC is actually called Blockchain 3.0, because solutions are no longer restricted to finance actions and assets transfer, but include the above-mentioned sectors and according expanded actions to support the logic behind them [18] [19].  So, with the rise of Blockchain 3.0 technology (2019) based on DAG data structures such as Byteball and IOTA, Blockchain systems are more efficient, scalable, highly interoperable, and have a better user experience than before. Among these sectors, government use cases are of special interest, because of the implications they introduce when adopting BC infrastructure to support them.With the rise of Blockchain 3.0 technology based on Directed Acyclic Graph DAG data structures [39], BC systems are more efficient, scalable, highly interoperable, and have a better user experience than before. Among the abovementioned sectors, government use cases are of special interest, because of the implications they introduce when adopting BC infrastructure to support them. These implications are coming from internal ones related to governmental issues such as politicians’ inaction and opposition, as well as external ones such as the unready for digital transformation laws and sensitive citizens’ and civil servants’ personal data [17]. The BC’s characteristics of decentralization providing zero down-time, immutability ensuring tamper-proof data, non-repudiation and security implemented with cryptography establishing trust between participating parties, consensus algorithms for data integrity, verification and satisfying scalability on private and permissioned blockchains [20] can be both accelerators and obstacles when applied to e-government EG applications.

It is obvious that BC 3.0 technology will support the evolution for EG to become Web 3.0 oriented, by providing the infrastructure, services and processes needed along with other Information and Communication Technologies [21] as Artificial Intelligence (AI) agents to secure and enhance communication between governments, businesses, and citizens [22]. EG 3.0 is totally depended to ICT and it evolves along with Web 3.0 technologies, which include but are not limited to blockchain, artificial intelligence, semantic web and text analytics, machine learning, internet of things, and big data analytics [23].

This paper will examine BC 3.0 and SC characteristics and features that are expected to affect EG 3.0 applications, as well as best practices on how to incorporate them while designing and implementing ICT Web 3.0 e-government solutions.

 II.        Blockchain

The two major forms of blockchain implementations are public permissionless and private permissioned BCs. The following sections will present the most important characteristics regarding EG 3.0 of both.

A.    Permissionless Blockchains

Permissionless BCs were the first generation of Distributed Ledger Technology DLT to provide decentralization as opposed to centralized databases. Bitcoin and Ethereum are the most known representatives of this kind of BCs. The concept is that all transactions are transparent to every participant and written on the ledger only after a consensus of the majority of peers has been achieved. Each participant shares an identical copy of this data called state, which is formed of blocks connected to each other through cryptographic hashes. This architecture makes it almost impossible to everyone to make even a small change to trick others about the data state and take advantage of the assets being exchanged without being noticed and the potential change being discarded by the other peers. A disadvantage of permissionless blockchains is that they do not have any control over who enters or leaves the network, this can be detrimental to security, driving to energy and time-consuming block generation techniques [11] in order to enforce security. The effect of such block generation techniques has the side effect the system to sacrifice its scalability and speed.

Nevertheless, permissionless BCs can be ideal for EG 3.0 applications when data must be public and transparent. Such use cases can be at the education area regarding certificates, degrees and diplomas issued by governmental organizations and academic institutions in order to be worldwide available, shared and verifiable [40][41]. Other uses can be the publishing of voting results, publicly available documents and copyrights.

B.    Permissioned Blockchains

Due to BC’s unique characteristics and especially the immutability and decentralization as argued before, the technology moved beyond the cryptocurrency aspect to cover other business needs such as asset tracking and logging, consent and agreement enforcement and monitoring, identity authentication and authorization. The problem with permissionless blockchains is that although they achieve a great deal of decentralization they can not guarantee the privacy and safety needed when dealing with sensitive citizen and government data. This is a direct result mainly from the lack of control on permissionless BCs of who can enter and leave the network at any time, making the complete history visible including confidential documents and records, as well as transactions containing personal citizens’ data.  

Permissioned Blockchains as HL Fabric answered the need for private and at the same time decentralized, secure, verifiable transactions between governments, citizens and businesses. The difference from the permissionless BC is that although all transactions are still written through smart contracts to the ledger, if someone needs to have access to the information permissions have to be given. A key aspect on permissioned BCs is that the participants are strictly controlled by a central authority, in an EG case a ministry or an independent authority. The participation to the network is completely controlled as well as who can do what with the ledger’s data. Blockchain policies exist on the network to grant permissions to stakeholders to perform specific actions. In example a citizen must be informed tha a public administration service wants to access her or his data and must consent, otherwise the access is not allowed. These actions are written on the blockchain, providing transparency but only to the participants that have the appropriate permission, in this case the specific public administration that requested the data and the specific citizen. Although permissioned BCs answer the need for privacy, scalability, security and speed some compromises have to be made in the terms of decentralization. Because a central authority is introduced to authorize the private network’s participants the decentralization is hindered and a BC controlling authority is introduced to the network [12].

Permissioned BC are ideal for governmental applications that require a level of security. It can be used for example to support the internal exchange of documents between public organization, keep track of inventories, registry or other private records.

 III.       Smart Contracts

Smart Contracts SC [13] are computer programs that are immutably written on the blockchain, can be called by the BC’s users. They provide the automation and control flow logic to any system BCs supports. Smart contracts must be treated as software functions in every aspect and smart contract BC engines must be deterministic. Determinism of SCs is the characteristic that maintains the ledger at a stable consistent state and is necessary to enforce transactions finality and avoid soft and hard forks [14]. The determinism of SC’s actions is usually left to the developer. Thus, she must make sure that the automated actions are executed as planned and the results of these actions leave the data in a consistent state, despite the node they are executed on.  Also, the SC’s actions must have the same result each time the SC is executed. In the writers’ opinion, which derives from empiricism, smart contracts can be categorized in three major kinds

  • Static,
  • Dynamic,
  • Oracle driven

Depending on the kind of the specific use case that has to be implemented, the developer designs either dynamic, or static or oracle driven smart contracts. Following, is a definition of each to explain the different characteristics in order to help researchers, architects and developers to decide which is the appropriate one in their case.

A.    Static standard output

Static SCs are the ones that do not call other smart contracts, do not reside on human interaction, include only one-step and are never going to change the predefined number of steps or actions. These are for example primitive math operations. Such SCs perform operations as addition, subtraction, multiplication and division. Other SCs can call them, retrieve and consume the result of this operation. All SCs receive parameters to perform their actions and from this point of view, they are somehow dynamic. However, there are no additional conditions embedded in this kind of SCs to change their path of actions. Math operations give each time the same result and operators follow the same precedence rules every time. Another kind of these SCs can also be a ‘yes/no” response to a specific question or a standard image returned when a button is pressed. An EG 3.0 application’s example is a function that accepts a verification number of an academic diploma and looks on the ledger for the diploma holder, the issuing institution and the date of issuance and return the result to the requester.

B.    Dynamic non-standard output

Dynamic are all the SCs that embed various rules allowing them to perform different actions according to these rules. Examples of such SCs are  functions that monitor certain conditions and trigger according actions. This can happen i.e. when a SC is utilized to monitor the electricity consumption and temperature logged on the BC of an energy smart building. The SC includes thresholds for different heating and consumption measurements in order to adjust the temperature in an eco-friendly way, avoiding excessive electricity consumption and costs. The following pseudocode can be part of the smart contract’s definition showing the logic behind monitoring and execution

if room_temperature < 18 Celcius {

  if electricity_consumption < 25 Watt

then turn_on air_condition

  else send_message: "The daily electricity consumption threshold has been reached. Would you like to turn on the A/C?"

    if user_answer == ‘YES’ then

            turn_on air_condition

 else do_nothing


if room_temperature > 25 Celcius {

  if electricity_consumption < 25 Watt

 then turn_on heating_unit

  else send_message: "The daily electricity

consumption threshold has been reached. Would you like to turn on the heating_unit?"

     if user_answer == ‘YES’ then

       turn_on heating_unit

  else do_nothing


This SC although deterministic, follows a non-static conditioned flow, which shows how a dynamic SC might be formed and how it can act. The aforementioned code is very simplistic but computer functions can be long and very complex. Additionally it involves human interaction, which in certain occasions could hinder or cancel the dynamic action feature of SCs. In our perspective the human input is considered dynamic to the terms of non-standard, condition driven final action. There are also other occasions where the dynamic nature of SCs is controlled by machine-to-machine M2M actions. This M2M interactions can have unpredictable outcomes when the developer’s design and implementation of the SC is erroneous, incomplete, or non-deterministic.

Another area of EG 3.0 applications that dynamic SCs can be used is to interconnect public administrations that need to exchange citizen data. For example, if the tax service wants to gain access to a citizen’s land titles which are kept by the land registry service, then a smart contract supplied with a VAT number from the tax service could look the land titles tied with this VAT number and return them to the tax service officer if he had the appropriate permissions. If a universal BC ledger containing the land titles for all citizens, then this could help to confront fraud and tax evasion and mediate the secure exchange of data between nations.

C.   Oracle driven

Both Static and Dynamic SCs handle data that resides on the BC itself. The third major category of SCs is the oracle driven ones which can handle data coming from sources external to the BC. This kind of SCs are dynamic in every way plus they include information brought into the system by the so-called AI oracles, which are smart contracts themselves. This special kind of SCs act as AI agents with the ability to inquire information from the real world and write it on the blockchain in order other smart contracts to consume it [24]. What is special about this SC category compared to the other is that SCs in general are not allowed to incorporate data external to the BC. The reason for this restriction is the determinism of BC functions. Determinism as argued before include the fact that the same result must be returned each time a SCs function is called, thus, we cannot reside to external resources which are subject to change. Thus, we mainly enforce determinism by using only data that currently exists on our ledger’s state. An exception to this is made through the oracles, by writing data on the BC to represent how this data was exactly at the time it was written on the ledger.

AI oracle driven SCs can be used in EG 3.0 law applications. For example, laws for inheritance can change and notaries or other public servants that are involved into the procedures regarding the transfer of the legacy to the legal inheritor must be formally informed. The oracle can look up information from a governmental repository and write to the BC when a specific law changes. After that a notification can be send through a BC 3.0 application to prove the date and time it was sent to inform the interested parties as well as ask and record on the BC their confirmation of receival.

 IV.    e-government 3.0

According to [25] definition, EG is the use of ICT to provide the means for governments, citizens and businesses to interact, communicate, share information and deliver services to the various stakeholders. EG 1.0 utilized the World Wide Web and available by then ICTs to become more efficient than it used to be [26]. EG 2.0 through portal services supported by Web 2.0 technologies became more citizen-centric, promoting citizens’ participation and enhancing e-democracy [27]. It becomes almost obvious by observing the technological evolution shaping EG, that  EG 3.0 will use Web 3.0 ICTs such as DLT, AI, Semantic Web and World Wide Virtual Web [20][28].  

Artificial Intelligence is another promising and disruptive technological field. The AI’s technological ability to equip machines with the cognitive capabilities to learn, infer and adapt depending on the consumed data is reinforced by the huge amount of information produced nowadays by smart devices, social media and web applications [29]. The problems governments, organizations and companies face while trying to leverage such huge amount of information is the centralization of data as well as the provenance of source legitimacy and authenticity. The data used in AI projects is centrally controlled, can be tampered and prominent to narrow not conscious emotionally driven AI, as the Microsoft’s AI twitter based bot project showed when it was overwhelmed with racist remarks which unfortunately repeated back to the users [30].

Taking under consideration [22] which argues that AI is thought as the solution of major governmental obstacles and specifically for resource allocation, large datasets, experts shortage, predictable scenarios, procedural and repetitive tasks, diverse data aggregation and summarization, it is crucial to research how to overcome the centralization, provenance and authenticity problems. The combination of BC and AI technologies can solve current centralization problems while in parallel can provide solutions for resource optimization and return private personal data control back to their respective owners in a distributed, decentralized and democratized manner [31].

The rest of this paper will examine two EG 3.0 scenarios supported by BC 3.0 and AI technology in order to provide EG stakeholders and policy makers ways to exploit current industry BC and AI applications for governmental, public and social good.

A.    Energy data – Scenario1

Governance of smart cities has been digitally enhanced during the last years by the use of ICT so key areas became subjects of research because of the increasing energy demands deriving from multiplication and complexity of the IoT devices. It became crucial for local governments to practice energy management strategies to use the available energy efficiently [32]. A modern smart city is a combination of smart technologies applied to its infrastructures and to citizens’ residences at building or even at home level. The ability of energy consumers to produce energy from renewable sources and distribute it through smart grids becoming thus prosumers increased the difficulty of national energy management techniques. However, in parallel it created an opportunity to make a smart city more sustainable and energy efficient if the additional produced energy is successfully modelled and incorporated to the city’s energy system, along with other energy elements as transportation and facilities [33]. This is so crucial that European Commission has published in the last years two directives for energy efficiency goals for a 20% energy savings target by 2020 and 30% energy efficiency target for 2030 along with specific national targets focusing on lowering energy bills, reducing nations reliance on external suppliers and becoming eco-friendlier protecting the environment [42][43]. With managing energy smart cities and supporting citizen-sourcing to achieve increased efficiency at all phases of the energy chain, the EG 3.0 will play a crucial role in the energy sector. BC 3.0 technology used in conjunction with AI provides authentication, decentralized intelligence, security and collective decision making.

The EG scenario is applied to a city, and includes IoT devices installed at citizens houses who are also prosumers. The IoT devices produce energy data which is stored on a private permissioned blockchain. As argued before the data stored on a BC is tamper-proof because it is cryptographically immutable and authenticated as each transaction is digitally signed. Energy data is considered confidential though, so the security concerns must be mitigated by using a private BC. The Know Your Customer KYC principle is provided through the permission policies enforced on the BC network by setting each citizen in charge of what is shared, either regarding personal data or energy production. More security can be enforced if the registration of prosumers follows a strict protocol, where the registration applications to participate at the local energy network and approvals from the city ’s local government are also logged on the BC. The whole process is automated through the use of Dynamic SCs controlling the processes of IoT data logging, registration and approval logging, available energy dispatching and monitoring.

A SC is used for gathering energy consumption and production measurements form the citizen’s IoT devices in order to log them on the blockchain. The citizen has to provide the BC identity that has been issued to her in order to login. This identity can be self-sovereign in order to be secure and remain at user’s control [44]. A SC is used for dispatching of the extra energy from a citizen’s residence to the main energy system or to the citizen-sourced smart grid she participates. If, for example, daily consumption needs are 14kWh and the SC detects that the power produced from renewable sources exceeds 15kWh, it can automatically trigger an action in order to dispatch this available power to the local energy system. In addition, there must be a dynamic smart contract to deposit the predefined amount of money for the energy dispatched by the citizen. Oracle based SCs can inform citizens when the energy dispatching can be more profitable, to provide incentives for participating to the energy network. Smart grids can be formed by local policies taking under consideration geographic factors, energy needs, and building production capabilities. AI agents will run at the citizens residences forming a collective decision making mechanism to apply Swarm Intelligence SI and achieve a swarm goal [34], programmed to decide how much energy can be dispatched to the city’s central energy system and how much energy can be traded among the participants on a smart grid. AI EG applications can read the data written on the BC and make forecasting of city’s energy needs for the next hours, days or even months. AI can also analyze the data and recognize trends and peak hours. The results and metadata from AI analyses can be grouped per district to help governments and policy makers create more efficient energy management strategies and achieve local and national goals.

Following is the pseudocode of two BC 3.0 SCs. The first one is for gathering energy consumption and production measurements form the citizen’s IoT devices in order to log them on the blockchain. The second is for energy dispatching of the excessive energy from a citizen’s residence to the main energy system, after checking the total consumption and total production which have previously been written on the blockchain. Both SCs are implemented on a private blockchain framework and take action every five seconds.

define SC_measurements():

  while True:{

           CurrentConsumption = IoT.get_measurements

           sign transaction(client_addr, CurrentConsumption )

           write to BC(client_addr, CurrentConsumption )

           CurrentProduction = IoT.get_production

           sign transaction(client_addr, CurrentProduction )

           write to BC(client_addr, CurrentProduction )


define SC_energy_dispatch(client_addr):

   while True:{

          energyConsumption = read BC.CurrentCons(client_addr)

          energyProd = read BC.CurrentProd(client_addr)

          if energyProduction > 10watt then

            if energyConsumption < energyProduction then

                dispatch = energyProduction – energyConsumption

                sign transaction{client_addr, dispatch}

                write to BC{client_addr, dispatch}


B.    Health data - Scenario 2

National Healthcare systems is another sector where e-health strategies must be adopted for governments to control excessive healthcare costs [35]. Healthcare systems include huge amount of data that are mostly confidential, thus, problems arise when trying to process and analyze those big data and AI is a perfect match to provide solutions to these problems. As research shows it is hard for older adults to use the e-health systems [36] [37]. By using AI chatbots, older people can use speech recognition to make questions and inquiries and the chatbots can provide guidance and responses. Another use for AI agents will be to get citizens’ filled forms and forward them to the appropriate government department [38]. As for the confidentiality and authenticity problems of the private e-health data, a permissioned BC 3.0 as it has been already described can provide the means to confront them. This way EG 3.0 can provide solutions to the e-health necessities by utilizing ICT and Web 3.0 to transform the legacy systems, in order to increase the efficiency and effectiveness of these systems, decrease costs and provide more citizen-centric health care services [36].

The EG scenario includes IoT wearables that send patient data, i.e. heart beats or blood pressure, to a private permissioned BC. This ensures the data’s security, authenticity and confidentiality. When a doctor wants to access the patients’ BC data she makes a request, which triggers a SC and this request is logged on the BC. The SC sends an information message to the patient and if the patient agrees to give access to the doctor the doctor gains access to the patient’s data. The SC writes on the BC the patients answer either it was positive or negative. This way a complete tracking system for requests and consent responses is formed. We can consider how useful and secure this can be when e-health records must be exchanged between countries at a national or international level with end-to-end security.

We can see an outline of three of BC 3.0 SC's pseudocode below:

define SC_health_data():

while True:{

      H_Data = IoT.get_heart_rates

      sign transaction(client_addr, H_Data)

      write to BC(client_addr, H_Data)


define SC_doctor_access():

  request read BC.H_Data(client_addr)

  sign transaction(doctor_addr, request, client_addr)

  write to BC(doctor_addr, request, client_addr)

  send inform_consent(client_addr, request, doctor_addr)


define SC_patient_consent(doctor_addr, request):

   read BC.doctor_request(doctor_addr, request)

   inquire response_from_patient

   if response == ‘YES’ then grant_access(doctor_addr for request)

   sign transaction(client_addr, response)

   write to BC(client_addr, response)


  V.        Further Research

We acknowledge that there are restrictions in our research, mainly due to the different energy and e-health implementations among countries in Europe. Our research focuses on governments and citizens, and further research has to be made in order to include results  and effects on public administrations and civil servants. The scenarios demonstrated are focused on BC 3.0 support. Thus, EG scenarios that include additional Web 3.0 technologies must be designed, developed and tested. We hope to be able to contribute more on these subjects as our research projects are still work in progress.

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