The startup develops a fleet information system that optimizes mobile mining operations by integrating motion tracking, financial control, and tonnage estimation across all equipment, including ancillary vehicles. This system enhances operational efficiency and reduces costs for the extractive industry by providing actionable insights typically found in more expensive solutions.
Funding
$780K 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
Mining operations often struggle with inefficient fleet management due to limited real-time data on equipment utilization, location, and performance, especially in environments where traditional GPS and WiFi networks are unreliable or unavailable. This lack of comprehensive data hinders effective decision-making, leading to suboptimal resource allocation and increased operational costs.
Solution
KMO Fleet offers a fleet management system designed to optimize mobile mining operations by providing real-time data and actionable insights, even in GPS-denied environments. The system uses an industrial Internet of Things (IIoT) approach with vehicle-to-vehicle communication, eliminating the need for extensive communication networks or reliance on satellite positioning. By integrating motion tracking, tonnage estimation, and financial controls, KMO Fleet enables mining operators to monitor equipment, analyze production trends, and improve overall fleet efficiency through data-driven decision-making. The system's modular design and AI-driven analytics convert sensor data into business events, facilitating short-interval control and continuous improvement.
Target Audience
The primary target audience includes mining operators and managers seeking to optimize their mobile mining fleets, improve operational efficiency, and reduce costs through data-driven decision-making.
Features
- OEM and equipment agnostic, compatible with various manufacturers, types, and ages of equipment
- Vehicle-to-vehicle communication for data routing, eliminating reliance on extensive communication networks
- AI-driven analytics to convert sensor data into actionable business events
- Real-time motion tracking to monitor equipment activity and utilization
- Tonnage estimation for production control and yield analysis
- Financial control tools to map costs against operational aspects
- Block model integration to track the grade of individual loads (for mining operations)
- Personnel management features to analyze shift compliance and safety applications
- Plug-and-play installation for quick deployment with minimal downtime
- Full data access for users to generate their own solutions and reports