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Develop Scalable Geospatial Cloud Platform for Farming as a Service
  1. case
  2. Develop Scalable Geospatial Cloud Platform for Farming as a Service

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Develop Scalable Geospatial Cloud Platform for Farming as a Service

spyro-soft.com
Agriculture
Environmental Services
Technology

Challenges in Commercializing Precision Agriculture Solution

Small Robot Company, having developed a prototype (Wilma) for intelligent crop monitoring and care, requires a robust and scalable geospatial cloud platform to support its commercialization efforts. The company needs a system to manage data collected from robots, analyze it using ML/AI, and provide actionable insights to farmers through high-resolution crop maps, all while enabling future expansion and increasing operational efficiency.

About the Client

A UK-based startup providing precision agriculture solutions through a Farming as a Service (FaaS) model, leveraging robotics, geospatial data, and machine learning for crop monitoring and care.

Project Goals

  • Develop a scalable and flexible geospatial cloud platform.
  • Enable real-time data ingestion and processing from robotic sensors.
  • Provide farmers with access to high-resolution crop maps and actionable insights.
  • Support the Farming as a Service (FaaS) business model.
  • Facilitate integration with future robotic fleets and data sources.
  • Improve farming profitability and reduce environmental impact.

System Functionality

  • Real-time data ingestion from robotic sensors.
  • Geospatial data storage and management.
  • Machine learning and AI-powered crop analysis.
  • High-resolution crop map generation.
  • User-friendly web interface for farmers to access data and insights.
  • Robot fleet management and scheduling.
  • Reporting and analytics dashboard.
  • Data visualization tools.

Preferred Technology Stack

Java (Backend)
React (Frontend)
GeoServer (Geospatial Data Server)
Cloud Platform (e.g., AWS, Azure, GCP - to be determined)
ML/AI Frameworks (e.g., TensorFlow, PyTorch)

Required Integrations

  • Robotic Sensor APIs (for data ingestion)
  • Mapping Services (e.g., Google Maps, OpenStreetMap)
  • Payment Gateway (for FaaS subscription management)

Non-Functional Requirements

  • Scalability to handle increasing data volume and user traffic.
  • High performance for real-time data processing and visualization.
  • Data security and privacy compliance.
  • Reliability and availability.
  • Flexibility to accommodate future technological advancements.

Expected Business Impact

The platform is expected to significantly improve Small Robot Company's ability to commercialize its FaaS offering, leading to increased revenue, enhanced customer satisfaction, and a positive impact on sustainable agriculture. By providing farmers with actionable insights, the platform will enable more efficient resource utilization, reduced environmental impact, and improved crop yields. The scalable nature of the platform will support future growth and expansion into new markets.

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