AISPOT
AISPOT provides an automated bioaerosol monitoring system that detects plant pathogens and airborne pollen before they become visible problems. The system combines the SporeScout autonomous sampler, SporeFinder AI-powered microscopy analysis, and a mobile app delivering results in approximately 35 minutes with 85% average model accuracy.
- Agriculture Technology
- Internet of Things
- Artificial Intelligence
- Data & Analytics
- Biotechnology
- Hardware
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Traditional plant pathogen detection relies on manual sampling and laboratory analysis, which is time-consuming, requires technical expertise, and provides only intermittent data. This delays critical decisions in crop protection and leaves growers vulnerable to undetected disease outbreaks that can spread rapidly.
Solution
AISPOT offers an end-to-end automated solution for continuous bioaerosol monitoring and pathogen identification. The SporeScout device operates autonomously in the field or indoors, collecting biological samples without manual intervention. Collected samples are processed by SporeFinder, which uses automated high-resolution microscopy and proprietary AI models to identify and quantify pathogens. All results are accessible through a cloud platform with continuous updates and notifications, transforming physical samples into actionable biological data. The system improves over time through constant learning, and each sample is linked to a unique QR code for full traceability of location and context.
Target Audience
Primary users are agronomists, crop consultants, and growers in viticulture, orchards, and greenhouse operations who need timely pathogen data to inform crop protection decisions, as well as building managers monitoring airborne pollen for human health protection.
Features
- SporeScout autonomous sampler that continuously collects bioaerosol samples in field or indoor environments without requiring technical skills, with 3-day battery autonomy and solar power option
- SporeFinder Pro analysis system using automated high-resolution microscopy and proprietary AI models for pathogen identification and quantification, processing each Frame in approximately 35 minutes
- AI models trained on real samples with dust and debris, achieving 85% average accuracy with verifiable spore images
- Cloud-based platform delivering results with continuous updates and notifications for real-time decision support
- QR-coded Frame system that links each physical sample to location and context data via the AISPOT mobile app
- Self-improving AI models that enhance detection accuracy over time through ongoing learning from collected samples
- Recognition of multiple pathogen targets including Alternaria, Venturia, and Cladosporium