Challenge Statement

Design and develop an integrated solution that leverages software-defined networking and IoT detection technology to monitor, predict, and/or manage Nutrient Loading of Lake Erie and its impacts in real time. 

The Problem – Harmful Algal Blooms and Phosphorus in Lake Erie

Phosphorus and nitrogen are essential elements for the growth of all organisms, but when large quantities are present, they pose a serious threat to ecosystem integrity. Excessive nutrient loads from agricultural fertilizer runoff have led to the growth of harmful algal blooms (HABs) in the western Lake Erie Basin. These mats of blue-green algae produce neurotoxins, including microcystins, with the potential to disrupt drinking water systems and kill wildlife. In 2015 Toledo’s entire water system was shut down for more than two days due to the presence of microcystin in the city’s water intake crib.

In 2016 the Great Lakes Water Quality Agreement (a bi-national agreement between the US and Canada) responded to this ecological crisis by setting a lake-wide target for a 40% reduction of phosphorus loading. In June of 2016, Ohio, Michigan and Ontario built upon the Agreement by signing a pact committing to reduce loading by 40% by 2025, with an interim goal of 20% by 2020. Now tasked with this huge challenge, the states, provinces, and localities of Lake Erie are beginning to implement strategies to reduce their P load and to measure those reductions.  

The Solution – Creating a monitoring system with SDN and IoT

Many agree that embedded monitoring devices and the Internet of Things (IoT) are the future of communications. With IoT’s focus on innovative sensors and real-time analytics, it seems like a natural fit for the challenge of monitoring nutrients and HABs. However, this space brings challenges of its own.

The recent explosion in IoT platforms has resulted in a fragmented technological landscape with challenges around interoperability and scalability. Any monitoring system will need to continuously incorporate a variety of detection technologies over its lifespan. Additionally, Lake Erie is more hostile than traditional IoT environments. A successful system will need to be both flexible and resilient, continuing to function unimpaired through storms, blooms, and other hazards.

Software-defined networking (SDN), a new approach to networking which separates the forwarding and control plane of the network, may help address these challenges. SDN takes network policy and puts it into a centralized software controller, allowing for a single network perspective, uniform configuration management and security policy, streaming telemetry and rapid adaptability to changing network conditions. As a result, SDN is more resilient, scalable, secure and reliable.

Additionally, SDN abstracts lower-level functionality, ensuring that managed devices are decoupled from the underlying network architecture. This layered architecture allows the network to integrate a broad variety of technologies without the compatibility issues that face conventional IoT operating systems. SDN has been shown to consistently and resiliently manage diverse technologies as well as provide a modular underlying infrastructure to augment with additional functionality later. If implemented, a nutrient monitoring SDN could expand to track a host of other pollutants and toxins. The infrastructure laid by this competition could, one day, create the first Smart Lake, empowered and connected by the Internet of H2O.

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