Towards a Green Digital Currency for Smart Communities:

An AI-Powered Ecosystem for Citizen Green Stewardship

Amira Kerkad

and Rabah Gouri

LSI-Computer Science Faculty USTHB, Algiers, Algeria

IECPS Lab – Department of Industrial Engineering & Maintenance, ENSTA, Algiers, Algeria

Keywords: Smart Communities, Circular Economy, Green Digital Currency, Sustainability, Digital Services, Artificial

Intelligence, Business Intelligence.

Abstract: This paper proposes a new ecosystem vision designed to measure and incentivize citizen and corporate

engagement in environmental stewardship through circular economy (CE). The ecosystem uses a gamified

platform where participants earn digital points for performing two types of operations: (1) recycling matters

and (2) reusing items, within smart communities. We propose to consider these points as a new global digital

currency redeemable for rewards and services offered by participating businesses worldwide. The businesses

are mainly the polluters that aim to have green advertisement and engagement in the "polluter pays" principle.

Consequently, these businesses will benefit simultaneously from green advertising and tax reductions. A suite

of digital services and AI-powered tools are used to optimize operations and generate valuable data for

improving both urban and rural sustainability initiatives. By making this new currency, we can assess

environmental engagement, motivate citizens to adhere into CE, and impose hierarchical participation in

sustainable practices. This paper outlines the ecosystem's components, discusses the feasibility of our proposal,

and explores its potential benefits and challenges for various stakeholders.

1 INTRODUCTION

The escalating global environmental crisis demands

innovative solutions to foster widespread citizen

engagement in sustainable practices. Traditional

approaches, such as education campaigns and

regulatory measures, often fall short in motivating

individuals to adopt environmentally friendly

behaviors. This paper introduces "Green Points," a

novel ecosystem that leverages gamification, digital

services, and AI to incentivize sustainable actions.

The new ecosystem operates as a digital platform

involving hierarchical participation, where

individuals earn points for completing

environmentally friendly actions. These points serve

as a digital currency that can be redeemed for rewards

and services offered by participating businesses,

particularly those with a history of environmental

impact. By incentivizing sustainable behaviors and

fostering a sense of community among different

actors, Green Points aims to contribute to the UN

https://orcid.org/0009-0003-0043-1345

https://orcid.org/0000-0003-3288-8529

Sustainable Development Goals (SDGs) defined for

2030 Agenda, namely:

- SDG 11: Sustainable Cities and Communities,

- SDG 12: Responsible Consumption and

Production,

- SDG 13: Climate Action,

- SDG 15: Life on Land,

- SDG 17: Partnerships for the Goals.

The ecosystem integrates digital services and AI-

powered tools to optimize operations, track

environmental impact, and generate valuable data for

improving urban and rural sustainability initiatives.

This data-driven approach enables informed

decision-making towards achieving a more

sustainable and equitable future for all, contributing

to the overarching goals of the 17 UN SDGs.

The paper begins by giving a brief literature

review in section 2. Then, in section 3, we outline the

framework of our proposal and delve inside each

component, followed by the ecosystem flow in the 4

section. Section 5 is dedicated to a developed

Kerkad, A. and Gouri, R.

Towards a Green Digital Currency for Smart Communities: An AI-Powered Ecosystem for Citizen Green Stewardship.

DOI: 10.5220/0013425800003953

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 14th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS 2025), pages 139-146

ISBN: 978-989-758-751-1; ISSN: 2184-4968

139

prototype called Snowber that serves as a local

platform in Algeria. Then we discuss big data

analytics, AI tools integration in section 6. The

potential and challenges of the proposal are provided

respectively in section 7 and 8. We conclude by

discussing the findings and exploring opportunities to

enhance our approach.

2 LITERATURE REVIEW

The circular economy (CE) is an economic model that

aims to eliminate waste and keep resources in use for

as long as possible. Unlike the linear economy, which

follows a "take-make-dispose" model, the CE

emphasizes recycling, reuse, and repair to minimize

resource consumption and reduce waste (Hungaro et

al, 2021). This approach promotes sustainability and

resilience by decoupling economic growth from

resource depletion and environmental degradation.

Ecological engagement refers to the active

involvement of individuals and organizations in

environmental protection and sustainability

initiatives (Genovese et al.2017; D'Amato et al. 2017;

Elia et al. 2017). For citizens, this can include

personal actions such as reducing waste, conserving

energy, and supporting sustainable businesses. For

businesses, ecological engagement involves adopting

environmentally friendly practices, reducing their

carbon footprint, and contributing to community

sustainability initiatives.

Governments play a crucial role in fostering

ecological engagement and promoting a circular

economy (D'Amato et al. 2017; Elia et al. 2017). They

can implement policies and regulations that

incentivize sustainable practices, invest in

infrastructure for waste management and recycling,

and support research and development in CE

technologies. Additionally, governments can raise

awareness about environmental issues and encourage

citizen participation in sustainability initiatives.

Many solutions have been proposed to promote

citizen recycling by rewarding them from engaged

companies through gamification (Oliveira et al. 2021;

Santos-Villalba et al. 2020), while also considering

the potential negative impact of gamification on green

consumption behavior (Shahzad, Xu, Rehman, et

al. 2024). But none has made a central solution where

all actors are connected together and use a local

digital currency.

On the other hand, the concept of "Smart

Community" originated in Silicon Valley, California,

in the early 1990s as a response to a severe economic

recession (Lindskog, H., 2004). Local leaders,

including businesses, community members,

government officials, and educators, collaborated to

revitalize the region. This collaborative approach to

addressing local challenges laid the foundation for the

concept of Smart Communities, which has since

gained global recognition. While the concept has

global applications, its implementation often relies on

local initiatives and community-driven solutions.

Numerous studies have investigated Smart

Communities and the role of Information

Communication Technology (ICT) in advancing

sustainability within smart homes and smart

manufacturing. For instance, Méndez et al. (Méndez,

et al. 2023) explored methods to encourage

sustainable behavior in smart homes by integrating

social interaction, personalized gamification, and

tailored Human-Machine Interfaces. Their research

aimed to enhance user engagement and overcome

barriers to adopting smart home technologies within

a community setting. Similarly, Sajadieh and Noh

(Sajadieh and Noh, 2024) acknowledged the

limitations of existing Industry 4.0 maturity models

in evaluating the unique aspects of Urban Smart

Factories (USFs), such as sustainability, resilience,

and human-centricity.

Policy and reform are key elements in Smart

Communities, besides smart data and innovation. A

Smart Community transcends geographical size. It

can encompass a local neighbourhood or extend to a

nationwide network, as long as the members share

common interests. This collaborative spirit is key.

Residents, organizations, and governing bodies all

work together to leverage ICT to improve their

community's circumstances, transforming their

collective reality through technological innovation.

While Smart Cities primarily focus on leveraging

technology to improve the efficiency and

sustainability of urban environments, Smart

Communities emphasize a more holistic approach

that prioritizes community well-being, social equity,

and environmental sustainability. Although distinct,

there's significant overlap between these concepts.

Many Smart City initiatives incorporate community

engagement and aim to enhance the quality of life for

residents.

Blockchain, the foundation of cryptocurrencies,

can enhance the CE by improving traceability,

transparency, and incentivizing sustainable actions

through tokenized rewards (Hakimi et al. 2024; Fang,

et al. 2022). While dedicated "green" digital

currencies does not exist yet, blockchain-based

platforms offer a promising avenue in Smart

Communities.

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Figure 1: Proposed Ecosystem for Citizen Green Stewardship. The Recycle/Reuse operations performed between citizen,

professional and associations empower the CE process, e.g., when a citizen performs a “reuse” operation, he gets green points,

which represent a currency exchangeable for rewards. Thus, the operations are rewarded by services and products from the

participant businesses. The businesses can also be rewarded by re-evaluating their taxes. AI tools and Data analytics

empowers the system at different levels.

In this article, we discuss a new global ecosystem

with a digital currency for Smart Communities where

all actors can be connected and assessed by governors

to encourage ecological actions and eco-responsible

advertisement for businesses. A decision support

system (

Jarke et al. 2013; Eboigbe et al. 2023)

integrated to provide relevant analytics for decision-

makers. AI tools are proposed to optimize and

manage related operations.

3 PROPOSAL

To explain our proposal, we illustrate the global

ecosystem in Figure 1. This ecosystem focuses on CE

enhancement through the collaboration of four key

actors composing Smart Communities:

•

Decision-Makers: The government actors

that evaluate different actors’ engagement

based on data analytics, and set rules on

operations, limits for green points, etc.

•

Stakeholders: All direct participating actors

in the recycling, collect, transformation or

reconditioning. They can be associations,

collectors, or supply chain workers.

•

Citizens: The core actors. They earn green

points for Recycling / Reusing actions.

•

Businesses: Any company that offers

rewards and services in exchange for Green

Points, and receive tax reductions.

The two main operations that are used to empower the

circular economy are Recycle and Reuse:

•

Recycle: this operation is dedicated to

matters, and is done between citizens and

environmental actors.

•

Reuse: this operation is dedicated to give a

second life for used articles, and it is done

between citizen or actors (associations,

reconditioners, renovators etc.).

We consider that other operations such as repairing,

renting or borrowing can be included under specific

Reuse actions.

4 ECOSYSTEM FLOW

The following list outlines the key stages of the Green

Points ecosystem flow, illustrating how citizen

actions, platform interactions, and digital services

work together to create a virtuous cycle of sustainable

behavior in a Smart Community. This dynamic

interplay of actions and processes drives the

ecosystem's effectiveness in achieving its broader

sustainability goals:

•

Actors’ interaction through the digital platform:

Citizens and associations/ professionals utilize a

digital platform to offer or search offers, or

connect with others users. The businesses use

the platform to propose rewards in exchange of

Towards a Green Digital Currency for Smart Communities: An AI-Powered Ecosystem for Citizen Green Stewardship

141

digital points. Decision-makers analyze the

participation of all actors and businesses.

•

AI-Powered optimization: AI algorithms (e.g.,

Genetic algorithms) optimize the collect journey

from different users in the neighborhood,

recommend the best offers (e.g., Classification),

match profiles of users with appropriate

partners, and facilitate efficient transactions.

Successful transactions are recorded, and the

number of Green Points is estimated depending

on the offer (e.g., Polynomial regression).

•

Data analytics insights & continuous

improvement: AI analyzes collected data to

provide insights for optimizing system

performance, improving efficiency, and

informing policy decisions. The system is

continuously refined based on data analysis,

user feedback, and emerging technologies.

This flow fosters a dynamic cycle of citizen and

business engagement, with AI tools, driving

sustainable behaviour within the community.

5 PROTOTYPE “SNOWBER”

To prove the applicability of our global ecosystem for

Smart Communities, we implemented a digital

platform that supports the new proposal. The platform

is called ‘Snowber’ - pine trees in Arabic-, and it is

designed to handle both recycling and reusing

operations (Figure 2). The separation between the two

operations is due to the heterogenous types of items

and users in each operation. For instance, recycling is

dedicated to waste (matters) when reuse is dedicated

to goods (second-life items). The other difference is

that recycling waste mostly involve matters recyclers,

when reusing goods can interest all kinds of users

(citizen, reconditioners, renovators etc.).

By doing so, we can partition the platform by

theme into two different mobile applications:

‘Snowber Recycle’ and ‘Snowber Reuse’, but yet find

almost the same functionalities. Citizens can use the

same account in both applications to keep track of their

activities. Each user of the mobile applications will get

a unique Green Code. This code is used to finalize

transactions between users when a collect is achieved.

This may avoid fictive accounts or transactions.

A policy of Green Points Credit attribution is set

to provide initial credit to associations and

professionals to enable making collects and transfer

credit to citizen.

Let us now delve into each step of the process as

illustrated in Figure 3:

1. User identification: The users can be either

citizen, associations or professionals of

recycling. A unique Green Code is given to users.

2. Choosing an operation from the main menu: (a)

Add an item by filling the form with its details

(photos, description, quantity, quantity unit,

price, price unit if not free, and location); (b) See

pending items of the user on the marketplace; (c)

Search for items by checking the marketplace

pages or dynamically on Maps; (d) See

conversations with other users; (e) Check

notifications about conversations, reservations,

points and rewards; (f) Edit profile

3. To add an offer or search for offers, the two

applications offer different categories depending

on whether it is recycled matter or reused item.

4. Choosing an item: The user can directly chat with

the owner to make reservation. After reservation,

the status of the item is visible to all users as

‘reserved’. The collector can optimize his

journey using maps to collect the maximum of

items he reserved on the platform. To finalize the

collect, the user provides his green code to the

owner to be introduced in the platform.

5. Getting points: Introducing the green code of the

user allows to finalize the collect, retrieve points

from the user to the owner and increment the

number of ecological operations for both users.

6. Getting redeemed: The businesses role now is to

reward citizen, to their ecological actions and

exchange credit with services or production.

7. Reevaluating taxes and stewardship of

businesses by decision-makers.

8. Reevaluating stewardship and Green Points

metrics are calculated based on historical data.

The platform has been tested over a six-month period

to validate the technical operations. However, full

validation depends on participating businesses in

order to collect real-world data and perform analytics.

Figure 2: Different types of goods considered in Reuse Mobile Application (Up) vs. different types of matters in Recycle

Mobile Application (Down).

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Figure 3: Prototype of Snowber Platform for Recycle/Reuse operations using two mobile applications (Reuse & Recycle) The

main actors interact with the platform by either using the marketplace (citizens, professional recycles or associations),

redeeming green points (businesses) or evaluating stewardship (decision-makers).

To illustrate the usage of our platform, let's consider

a use case centered around Snowber Recycle (Figure

4), our application dedicated to recycling. Note that

the process for Snowber Reuse is similar, with the

primary difference being the types of items involved.

A visitor can explore the marketplace without

logging in. However, to interact with offer or create

new offers, they must log in as either a citizen or a

professional/association.

The marketplace offers two primary methods for

exploration:

•

List View: Users can scroll through a list of

items sorted by price, distance, or type. This

provides a traditional browsing experience.

•

Map View: This interactive map visually

displays nearby offers, allowing users to

easily identify items of interest within their

vicinity.

Once a user selects an item, they are presented

with detailed information, including its type, price,

quantity, and a description. To initiate a transaction,

the user can contact the owner through an integrated

chat system to discuss reservation details.

If the owner accepts the reservation request, he

will update the item's status to "reserved," preventing

other users from claiming it. This ensures a smooth

and efficient transaction process and avoid

unnecessary contacts.

When the user retrieves the item, he exchanges the

unique Green Code with the owner. This code serves

as a digital token to finalize the transaction and record

the exchange on the platform.

Upon successful completion of the transaction, the

platform automatically allocates Green Points to the

owner based on the type and quantity of the item.

These points can be redeemed for various rewards or

used to support future recycling initiatives.

6 BIG DATA & AI

Smart data plays a crucial role in enabling Smart

Communities. To effectively leverage this data, the

integration of AI tools is essential. Furthermore,

operating on a large scale necessitates a robust

decision-making framework underpinned by

powerful analytics and the capacity to process large

datasets. This section outlines key analytical

requirements and proposes a target schema for a data-

warehouse to facilitate informed decision-making.

We then explore the potential integration of AI tools

within our ecosystem.

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Figure 4: Example of the prototype deployment of Snowber Recycle Application. From left to right, the first image shows

the home page for a visitor user. The second image shows the market place dedicated to matter offers. The third image shows

the market place on maps. The last image shows details of a selected offer.

6.1 Data Analytics

The analytics to be done by our decision support

system are mainly:

•

Environmental and social research: The

system helps providing valuable data on

recycling trends, patterns, and impacts. It

also analyzes recycling rates, quantities, and

types by region, time, and user category.

•

Employment analysis: It allows tracking

employment trends in recycling-related

fields (e.g., collection, distribution, etc.) and

analyzing employment rates by type, region,

and time.

•

Food waste analysis: Analyzing food waste

quantities, types, and locations. And

consequently, identifying patterns and

trends for food waste reduction strategies.

•

Health impact analysis: Analyze potential

health problems related to environmental

factors (e.g., pollution, waste exposure etc.).

Consequently, identify areas of concern and

develop targeted interventions.

•

Efficiency analysis: Compare the efficiency

of traditional waste collection methods with

geo-localization-based approaches. Then,

evaluate the impact of optimized collection

routes on resource utilization and

environmental impact.

6.2 Data-Warehouse Design

To support our decision-making process, we design a

data-warehouse dedicated to provide the previously

listed analytics for decision-makers (e.g.,

governments, industrials and scientists).

After defining the target analytics, the next step is

to select the data sources for integration. For this step,

we choose to use the operational databases of our

platform. The target schema of the data-warehouse to

be designed can be defined as follows:

•

Dimensions: The selected dimensions for

our decision support system are time (Date,

month, year, hour, day of week), type of

materials/goods (offer (paper, plastic,

electronics, etc.), localization (geographical

location e.g., country, region, city), user type

(citizen, professional or association) and

demographic information (age, gender,

income).

•

Fact table: The main facts are

Recycling/Reusing operations. The

corresponding measures are the number of

offers and quantity per type.

6.3 AI Tools Integration

AI techniques can be used to regularly re-evaluate the

weight of Green Points, transactions efficiency and

environmental impacts depending on existing data.

The more the platform is used, the more relevant and

valuable the data becomes. In the following, we

provide some AI tools integration possibilities:

•

Recommendation and optimization: Machine

learning techniques can be used to match the

most suitable recyclers or reuse partners based on

location, item type, and availability. Meta-

heuristics can also be used to optimize collection

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routes for recyclers, minimizing travel time and

fuel consumption.

• Predictive analytics: Forecasting recycling

trends, and predict resource needs.

• Fraud detection and prevention: Using

anomaly detection techniques allows identifying

suspicious activities, such as fraudulent point

accumulation. Image recognition can be used to

verify the authenticity of recycled materials.

• Enhance user experience: Chatbots and virtual

assistants provide instant support and guide users

through the process.

7 POTENTIAL

The proactive engagement of all stakeholders within

the ecosystem will strengthen all links in the circular

economy chain, laying the foundation for a smart

community. This positive impact is anticipated to

have significant repercussions across various sectors.

Here we outline a non-exhaustive list of some of the

expected positive outcomes of our proposal:

• Ecological impact: The new ecosystem will

significantly impact the environment by

enhancing recycling efforts. This includes

optimizing collection routes to minimize fuel

consumption and emissions, encouraging source

separation of waste to improve material quality,

and ensuring proper management of toxic waste

to prevent environmental contamination.

Furthermore, the system will promote

sustainable manufacturing practices (repairing,

reconditioning, and sustainable production).

• Social impact: The new system can significantly

enhance social well-being by generating

employment opportunities in the CE, including

waste collection, processing, and distribution. It

promotes improved working conditions for waste

collectors, fostering a more dignified and safe

working environment. Ultimately, the new

system contributes to a higher quality of life by

creating a healthier environment.

• Economic impact: Improved environmental

quality can lead to significant economic benefits.

Lower healthcare costs can be realized due to a

decrease in illnesses linked to environmental

factors, such as respiratory diseases and certain

cancers. This translates to lower insurance costs

for individuals and businesses as reduced

environmental risks diminish the likelihood of

health claims. Moreover, by promoting efficient

waste management and reducing the need for

costly disposal methods, the system can help

municipalities significantly lower their spending

on recycling and waste treatment programs. For

businesses, this system is more advantageous

since they use green advertising instead of

investing in costly advertising campaigns.

8 CHALLENGES

Realizing the full potential of the Green Points

ecosystem will require long-term commitment and

collaboration from various stakeholders. The

implementation of the new ecosystem will inevitably

encounter challenges that require careful

consideration and proactive planning to overcome

potential obstacles and maximize the positive impact

of the system.

This section provides the key challenges facing

the successful implementation of the ecosystem:

• Decision-maker involvement: Active

participation from government agencies and

policymakers are crucial for the successful

implementation and scaling of the system.

• Blockchain technology: Exploring the potential

of blockchain technology can enhance

transparency, security, and immutability in the

management of digital points and transactions.

Blockchain's immutable and decentralized nature

ensures that all transactions involving Green

Points are recorded transparently and publicly

verifiable. This eliminates the possibility of data

manipulation or fraudulent activities.

• Cryptocurrency: Cryptocurrency can facilitate

cross-border Green Point exchanges, fostering a

global network of sustainable practices and

providing financial inclusion for underserved

communities. However, volatility and regulatory

challenges exist. Utilizing stablecoins and

closely monitoring the regulatory landscape are

crucial for mitigating these risks and ensuring the

long-term success of cryptocurrency integration.

• Interoperability: Integrating the system with

existing smart city infrastructure, such as public

transportation and waste management systems,

can enhance efficiency and user experience.

• Data privacy and security: Ensuring the secure

and ethical handling of user data is paramount.

Robust data privacy and security measures must

be implemented and regularly audited.

• Transparency and trust: Maintaining

transparency in all system operations is critical

for building and maintaining trust among all

stakeholders.

Towards a Green Digital Currency for Smart Communities: An AI-Powered Ecosystem for Citizen Green Stewardship

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• Scalability and sustainability: The system must

be designed to accommodate a growing user base

and evolving needs while ensuring its long-term

sustainability and environmental impact.

While many challenges exist, the potential benefits

warrant a concerted effort to address them

proactively.

9 CONCLUSIONS

This paper introduces the "Green Points" ecosystem,

a novel gamified platform designed to incentivize and

measure citizen engagement in sustainable practices

within a circular economy framework. By rewarding

environmentally friendly actions like recycling and

reusing, the system motivates individuals to adopt

eco-conscious behaviors. Green Points, functioning

as a digital currency, can be redeemed for rewards and

services offered by participating businesses.

The proposed ecosystem offers significant

benefits to various stakeholders:

• Citizens: Increased motivation for

sustainable actions, access to rewards and

services, and a sense of community

involvement.

• Businesses: Enhanced brand reputation

through "green advertising," potential tax

reductions, and increased customer loyalty.

• Communities: Sustainable and healthier

environment, with more job opportunities

within the circular economy sector.

The paper explores the core components of the

Green Points ecosystem, including its gamification

mechanics, digital currency system, and stakeholder

engagement strategies. The feasibility of the system

is demonstrated through the development of a

prototype platform, "Snowber" composed of two

mobile applications. By leveraging big data analytics

and AI tools, the system can be continuously

optimized to maximize its impact.

To fully realize the potential of the new

ecosystem, further research and development are

crucial. This includes investigating the integration of

emerging technologies such as blockchain and

cryptocurrency, exploring its economic viability and

policy implications, and developing strategies for

large-scale implementation. Future research should

also delve into considering other metrics (e.g., carbon

credits), the long-term sustainability of the system,

and exploring the potential for cross-border

collaboration to foster a global network of sustainable

practices, ultimately contributing to the emergence of

a global, interconnected smart community.

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