We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
The Smart Drifter Cluster: Monitoring Sea Currents and Marine Litter Transport Using Consumer IoT Technologies
AI summary Read the abstract
Researchers introduced a Smart Drifter Cluster concept — low-cost IoT-enabled floating sensors — to track ocean currents and monitor the transport of marine litter and plastic debris. This technology could provide real-time data on microplastic distribution across coastal and open ocean environments.
The study of marine Lagrangian transport holds significant importance from a scientific perspective as well as for practical applications such as environmental-pollution responses and prevention (e.g., oil spills, dispersion/accumulation of plastic debris, etc.). In this regard, this concept paper introduces the Smart Drifter Cluster: an innovative approach that leverages modern "consumer" IoT technologies and notions. This approach enables the remote acquisition of information on Lagrangian transport and important ocean variables, similar to standard drifters. However, it offers potential benefits such as reduced hardware costs, minimal maintenance expenses, and significantly lower power consumption compared to systems relying on independent drifters with satellite communication. By combining low power consumption with an optimized, compact integrated marine photovoltaic system, the drifters achieve unlimited operational autonomy. With the introduction of these new characteristics, the Smart Drifter Cluster goes beyond its primary function of mesoscale monitoring of marine currents. It becomes readily applicable to numerous civil applications, including recovering individuals and materials at sea, addressing pollutant spills, and tracking the dispersion of marine litter. An additional advantage of this remote monitoring and sensing system is its open-source hardware and software architecture. This fosters a citizen-science approach, enabling citizens to replicate, utilize, and contribute to the improvement of the system. Thus, within certain constraints of procedures and protocols, citizens can actively contribute to the generation of valuable data in this critical field.
More Papers Like This
Towards an IOT Based System for Detection and Monitoring of Microplastics in Aquatic Environments
AI summary Read the abstract
This paper proposes using Internet of Things (IoT) sensors to build a real-time monitoring network for microplastics in aquatic environments. Automated, continuous monitoring systems could provide much better spatial and temporal coverage than current sampling-based approaches.
Microplastics Detection in Soil and Water: Leveraging IoT Technologies for Environmental Sustainability
AI summary Read the abstract
Researchers explored the integration of IoT sensor technologies for detecting and monitoring microplastics in soil and water environments, proposing a connected sensing framework for real-time environmental surveillance. The system enables automated data collection and remote monitoring of microplastic contamination.
IoT Driven Smart Innovation for Microplastic Monitoring and Detection: A Multidimensional Review
AI summary Read the abstract
This review evaluates IoT-integrated systems for real-time microplastic monitoring and detection in water, covering sensor technologies, predictive modeling, and risk assessment frameworks applied to common polymer types including PP, PE, PVC, and PET. Scalable IoT-based detection infrastructure could transform environmental monitoring from periodic sampling to continuous surveillance, enabling faster regulatory response to microplastic contamination events.
Smart buoy technology: a versatile platform for connected ocean operations.
AI summary Read the abstract
Researchers describe how smart buoy technology from Blue Ocean Gear brings real-time GPS tracking and sensing to commercial fishing gear, directly reducing ghost fishing by enabling rapid recovery of lost traps and nets that would otherwise continue catching marine life and contributing to ocean plastic pollution.
Real-time detection of microplastics in aquatic environments using emerging technologies
AI summary Read the abstract
Researchers proposed a real-time microplastic detection system combining AI-enhanced optical sensors and IoT devices, capable of automatically classifying microplastics in ocean water without the time-consuming manual steps required by spectroscopy or microscopy.
Research digests by email
When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.