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Innovative strategies: AI-powered sustainable smart farming

Explore how cutting-edge AI-driven sustainable farming and offer lifecycle management are revolutionizing the agriculture industry.

NTT DATA uses Generative AI capabilities to address one of many critical Communications Service Providers (CSPs) challenges: creating new monetization avenues. AI-powered sustainable smart farming is one way for CSPs to provide proactive, preventive and prescriptive care to agro companies. Smart Farming as a Service (SFaaS) integrates advanced connectivity, data analytics and Generative AI to foster sustainable agriculture by using a dynamic B2B2X model, integrated sensors and automated systems to enhance farming efficiency.

Index

1. The future of AI and GenAI for telco operators

The integration of AI and GenAI is poised to revolutionize the telecommunications industry, offering a plethora of opportunities for improving operations, customer experience and overall efficiency. Here's a look at the key areas where AI and GenAI will drive future transformations for telco operators:

  1. Improved customer experience

    • Personalization: AI can analyze customer data to provide highly personalized services, offers and support, improving customer satisfaction and loyalty.
    • Chatbots and virtual assistants: Advanced AI-powered chatbots and virtual assistants can handle customer queries efficiently, providing instant support and freeing up human resources for more complex tasks.

  2. Operational efficiency

    • Predictive maintenance: AI can predict equipment failures before they occur, allowing for proactive maintenance and reducing downtime.
    • Network optimization: AI algorithms can improve network performance in real time, ensuring better service quality and efficient use of resources.

  3. Cost reduction

    • Automation: Automating routine tasks and processes with AI reduces operational costs and minimizes human error.
    • Resource management: AI can optimize resource allocation, from energy use to bandwidth distribution, cutting unnecessary spending.

  4. Data analytics and insights

    • Big data: AI can process vast amounts of data to uncover insights that drive strategic decision-making and competitive advantages.
    • Customer insights: Understanding customer behavior and preferences through AI analytics allows for targeted marketing and improved service offerings.

  5. Security enhancements

    • Fraud detection: AI can detect and mitigate fraudulent activities in real time, improving security for operators and their customers.
    • Network security: AI-driven security systems can identify and respond to threats more quickly and accurately than traditional methods.

  6. Sustainability and environmental impact

    • Energy efficiency: AI can optimize energy use across networks, reducing the carbon footprint of telco operations.
    • Sustainable practices: Integrating AI with sustainable initiatives can help telcos achieve their environmental goals, such as reducing emissions and managing waste more effectively.

  7. New revenue streams

    • AI services: Offering AI-driven services and solutions to other industries opens up new revenue streams.
    • Smart solutions: Developing smart solutions for sectors like agriculture, healthcare and smart cities by using AI technologies can expand business opportunities.

  8. Future innovations

    • 5G and beyond: AI will play a crucial role in the deployment and optimization of 5G networks and future communication technologies.
    • Edge computing: Combining AI with edge computing can bring data processing closer to the source, reducing latency and improving real-time decision-making.

As AI and GenAI technologies continue to evolve, telco operators are set to experience unprecedented levels of innovation and efficiency, transforming their operations and the services they provide to their customers. This future-forward approach not only benefits the telecom industry but also contributes to broader societal and environmental goals.

This article focuses on how NTT DATA has been working with CSP clients and partners to realize the future with AI/GenAI, especially in the areas of new revenue stream and sustainability for CSPs. For further We leverage the innovative partnership NTT DATA is an active member of TM Forum Catalyst projects, collaborating with CSP clients and partners to pursue this ambition. In the recent TM Forum Catalyst project, we focused on agriculture industry as an industry which can benefit from introduction of AI/GenAI.

2. Current situation in the agriculture market

Telecom GenAI Revolution (2:16)

Market trends in agriculture ecosystem:

  1. Collaborative ecosystems: There is a growing trend toward creating collaborative ecosystems involving agricultural companies, telecom operators and IoT suppliers to provide comprehensive smart-farming solutions.

    • The global smart-farming market was valued at about $13.8 billion in 2021 and is expected to reach $26.8 billion by 2027, growing at a compound annual growth rate of 11.2% from 2022 to 2027.
    • Over 50% of large agribusiness firms have engaged in strategic collaborations with technology providers, including telecom operators and IoT suppliers, to develop smart-farming solutions.
    • Telecom operators and IoT suppliers have increased their research and development spending by over 15% annually to develop and integrate smart farming technologies.

    Sources: Market Research Report on Global Smart Farming Market (2022), Statista Report on Smart Agriculture Market Size (2022)

  2. Regulatory support: Governments and regulatory bodies are increasingly supporting the adoption of AI and IoT in agriculture through subsidies and policy initiatives.

    • The European Union's Common Agricultural Policy allocated approximately €40 billion in subsidies for precision farming technologies between 2021 and 2027.
      Source: European Union Common Agricultural Policy (CAP) 2021-2027
    • The US Department of Agriculture provided over $900 million in grants and loans in 2022 to support the adoption of advanced farming technologies, including AI and IoT.
      Source: USDA Grants and Loans Report 2022
    • India announced a $1.4 billion fund in 2021 to promote digital agriculture and the integration of smart technologies in farming practices.
      Source: Government of India's Digital Agriculture Fund Announcement 2021
  3. Consumer awareness: Rising consumer awareness about sustainable farming practices is driving the market for smart-farming solutions.

Challenges:

For agriculture industry clients, their main challenge is to maximize crop yield and minimize carbon emission, but at the same time, they want to optimize cost through efficient agricultural practices.
For the Agriculture solution providers, they want to support the agriculture industry clients by providing their services effectively and efficiently. In order to do so, agriculture solution providers want to establish strategic business leading CSPs for enhanced operational efficiency and robust connectivity, while creating new business opportunities and revenue.
To resolve above challenges, NTT DATA joined the Catalyst project for Smart Faming to foster a more sustainable agriculture model, optimizing energy & resources while promoting a greener future. To achieve it, Telco Industry plays a crucial role by developing and commercializing Smart Farming as a Service (SFaaS) solution that integrates advanced connectivity with data analytics and GenAI and 3rd Parties Agro Specific Solutions.

3. AI-powered sustainable smart farming

The Future of Smart Farming (3:57)

In the relentless pursuit of sustainability and profitability in agriculture, this Catalyst project harnesses cutting-edge technology to revolutionize the industry. At the heart of this endeavor lies Generative AI, a pivotal part of our innovative approach to farming. In this blog, we delve into the key technological details, architecture design, ROI models, business outcomes and the potential impact of our initiative on the agriculture industry.

Figure 1: Team members and key pillars of the catalyst project

We believe telecom operators (CSPs) are at the forefront of the next generation of network transformation, and one of the most promising avenues for innovation is through AI-powered sustainable smart farming that uses Generative AI and predictive analytics. By developing a SFaaS solution, CSPs integrate advanced connectivity, diverse data inputs and sensor integration to improve energy and resource use.

Here's how CSPs can leverage these technologies to drive network transformation:

By leveraging Generative AI and predictive analytics, CSP's can facilitate proactive, preventive and prescriptive measures across various farming scenarios. This enables the development of a Smart Farming as a Service (SFaaS) solution that combines advanced connectivity with data analytics and third-party agro-specific solutions.

The aim is to promote a sustainable agricultural model that improves energy and resource use while fostering a greener future. By anticipating environmental conditions, this approach empowers farmers to make proactive decisions, helping them prepare for and adapt to changing circumstances. Ultimately, it ensures optimal crop yields and effective resource management.

CSPs can develop an SFaaS solution that integrates:

  1. Advanced connectivity: Ensuring robust and reliable communication channels for data transmission.
  2. Diverse data inputs: Using various data sources to provide comprehensive insights.
  3. Sensor integration: Implementing sensors to monitor and improve energy and resource use in real time.
  4. Anticipating environmental conditions: Helping farmers to stay ahead of weather changes and other environmental factors.
  5. Enabling proactive decision-making: Allowing farmers to make informed decisions to improve crop yields and resource management.

Architecture design of AI-powered sustainable smart farming:

Figure 2: Smart Farming as a Service architecture

Diverse data inputs

Several data inputs fuel our solution, including:

  • Product catalog and inventory information: This data helps in managing stock and availability of farming products.
  • Charging-related data: Vital for understanding and managing energy consumption.
  • Partner relationship management systems: Information about partner products like pesticides and fertilizers, which are recommended to agricultural companies based on need.
  • External sources: Weather data, historical terrain and climatic conditions, and water sources are crucial for accurate predictive analytics and decision-making.

This data is used to inquire about available offers and pricing, and to generate corrective offers tailored to individual farming needs.

Key use case: Dynamic lifecycle adaptation

Dynamic lifecycle adaptation is a revolutionary approach that uses the power of GenAI to transform intelligent farming and analyze critical crop data points (stages, growth patterns, pest infestations, fertilization needs and more).

Through continuous data analysis, GenAI identifies the exact needs of the crops and uses a simple chat interface to propose actionable changes to the agriculture operator. This seamless integration into farm management enables proactive, data-driven decisions that enhance productivity and sustainability, keeping the farm a step ahead in meeting its evolving demands.

Figure 3: Dynamic Lifecycle Adaptation concept

4. Business Outcomes

Our solution aims to deliver quantifiable business outcomes and success metrics, including:

Figure 4: Business outcome of Gen AI

Potential impact on industry

The potential impact of our Catalyst solution in revolutionizing and solving the challenge is profound:

  1. Elevated consumer advantage

    As consumer preferences pivot toward organic and sustainable choices, automated farming emerges as a catalyst for delivering faster, fresher and more ecofriendly produce. The heightened productivity resulting from automation increases overall yield and drives down costs for consumers.

  2. Streamlined labor operations

    In a landscape where labor makes up over 50% of farming expenses and labor shortages affect 55% of farmers, the integration of harvest machine learning offers a transformative solution. Automating routine tasks through robotics technology significantly cuts down on labor costs. For instance, a single strawberry robot harvester can cover a 25-acre area in just three days, effectively replacing the need for 30 farm workers.

  3. Sustainable agricultural practices

    Automated farming not only bolsters profitability but also aligns with sustainable agricultural practices. Through precision farming techniques, farmers can judiciously apply pesticides and fertilizers, reducing the environmental impact on soil and water. Automated systems contribute to energy and water conservation to diminish the overall environmental footprint of farming.

  4. CSP efficiency advantages

    By adapting resources to real-time requirements, automated farming ensures the judicious use of resources for platform services. This adaptability enhances the efficiency of the platform, paving the way for a more responsive, resource-efficient and streamlined ecosystem.

5. The evolution of our GenAI-powered sustainable farming initiative

NTT DATA's initiative represents a groundbreaking fusion of advanced technology, data-driven insights and sustainable practices. It is poised to reshape the agriculture landscape for the better. By using GenAI and a comprehensive approach to resource management, we aim to elevate the customer experience, reduce costs and improve the quality and reliability of agricultural operations. The transformative potential of our solution promises a brighter, more sustainable future for farming, benefiting both stakeholders and society.

Future phases and expansion

In future phases, we aim to expand our solution's scope to:

  1. Encompass carbon savings: By integrating carbon tracking and reduction mechanisms, we strive to minimize the carbon footprint of agricultural practices and promote ecofriendly farming.
  2. Economic benefits: Our continuous refinement of GenAI algorithms and resource management strategies will drive down operational costs and enhance profitability for farmers, contributing to the economic sustainability of the agriculture industry.
  3. Maximize positive impact: By extending the capabilities of Catalyst, we will amplify its positive effects on agricultural production and society at large, fostering a more resilient and sustainable food system.

Through these enhancements, our initiative will not only support the agriculture industry's growth but also address broader societal and environmental challenges, paving the way for a sustainable future.

Luis Fernando Rubio Martinez

Telecom Executive Director

Related links

TM Forum

Catalyst Home page