KonSat-1: Multisensor System for Detecting Oil Pollution from Ships Using Optical and AIS Technologies

Manayay J.L.S.; Bett J.S.P.; Quiñones A.J.A.; Fernandez L.A.V.; Suazo F.Á.C.; Butron E.G.S.; Zaidman J.C.C.; Chávez R.G.C. · Proceedings of the International Astronautical Congress, IAC (2025) · DOI: 10.52202/083084-0035

Resumen

Oil spills and harmful algal blooms represented critical threats to marine ecosystems. According to the International Tanker Owners Association, 215 significant hydrocarbon spills (over 100 tons) were recorded between 2010 and 2023. This situation demanded cost-effective solutions for real-time monitoring, and CubeSats, with their versatility and low cost, emerged as innovative platforms for environmental surveillance. This work presented KonSat-1, developed by the UNI-SAT team at the National University of Engineering for the CubeDesign Competition. The satellite was designed to detect marine pollution through a hybrid fusion of optical sensors and Automatic Identification System (AIS) data. It integrated a near-infrared (NIR) optical system to identify oil spills and algal blooms using specialized spectral indices, while an AIS receiver tracked vessel positions to spatially correlate spills with potential sources. A high-capacity microprocessor processed integrated multisensor data using a deep learning algorithm based on a convolutional neural network. Thermal and structural resilience was validated through vacuum simulations, vibration testing, and radiation resistance analysis. Additionally, an analysis of the performance of the Telemetry, Power, and Control subsystems in relation to the mission’s orbital parameters was proposed for future work. Multisensor processing significantly improved detection accuracy compared to unimodal methods, and onboard processing reduced data latency, optimizing emergency response windows. Testing confirmed operational stability. KonSat-1 demonstrated a scalable architecture for maritime monitoring by integrating embedded intelligent algorithms and an automated alert system, which sent real-time information to the ground station to enable immediate response. Its modular and low-cost design established an innovative model for proactive environmental management, prioritizing the protection of vulnerable ecosystems.

Instituciones: Universidad Nacional de Ingeniería