The startup operates a carbon footprint monitoring platform that utilizes integrated sensor hardware, an AI engine for anomaly detection, and a cloud-based analytics interface to capture and process real-time environmental data. This system enables clients to accurately measure and model air quality, leading to scientifically validated actions that improve public health and well-being.
Funding
$750K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Current methods for monitoring air quality and carbon emissions often lack the granularity and real-time data needed to effectively measure and manage environmental impact. Existing solutions may not provide the localized, continuous data necessary to pinpoint emission sources and assess the effectiveness of mitigation strategies.
Solution
Edgeliot offers a comprehensive platform for real-time air quality and carbon footprint monitoring, leveraging a network of IoT sensors, edge computing, and cloud-based analytics. The system provides continuous, hyper-local measurements of key environmental parameters, including particulates, CO2, methane, nitrous oxide, temperature, pressure, humidity, wind speed, and direction. By integrating edge AI and advanced data analytics, Edgeliot enables users to identify emission sources, track trends, and measure the impact of environmental policies. Data is securely stored in a scalable Microsoft Azure environment and visualized through a user-friendly interface, providing actionable insights for informed decision-making.
Target Audience
Edgeliot's primary customers include environmental agencies, municipalities, industrial facilities, and telecommunication companies seeking to monitor and manage air quality, reduce carbon emissions, and assess climate risk.
Features
- Real-time monitoring of particulates, CO2, methane, nitrous oxide, temperature, pressure, humidity, wind speed, and direction
- Hyper-local measurements for precise identification of emission sources
- Edge computing algorithms for on-site data processing and anomaly detection
- Secure data storage and scalable infrastructure on Microsoft Azure
- Real-time data visualization accessible via smart devices
- Air Quality Index (AQI) calculation based on biogenic volatile organic compounds and CO₂ equivalents
- Integration of wind speed and direction data to pinpoint emission origins
- Optional image capture capabilities for specific applications
- Built-in accelerometers and gyroscopes to capture infrastructure motion
- API access for licensed data integration into external systems