Problem statement our technological product seeks to address [STATEMENT / PROBLEM 3]

Aquatic invasive species present a major ecological and economic threat throughout the world. In North America, a group of four large and voracious fish species collectively known as the Asian carps are currently threatening to invade the Great Lakes. The Great Lakes are the world's largest freshwater system and are home to more than 100 species of native fishes and a multi-billion dollar fishing industry. Canada and the United States are working together to prevent Asian carps (Bighead Carp, Silver Carp, Grass Carp and Black Carp) from entering the Great Lakes. Prevention is more effective and much less costly than trying to control an invasive species after it arrives.

Asian carps have already caused great ecological and economic damage in the Mississippi River basin where they have already invaded. A 2011 'Binational Ecological Risk Assessment for Bigheaded Carps in the Great Lakes' showed that the Great Lakes are at high risk of invasion by Asian carps and that ecological consequences could be high. In this risk assessment, high risk tributaries were identified by computer modelling and many of these tributaries have been sampled for Asian carps between 2013 and 2015 as part of Fisheries and Oceans Canada's early detection surveillance program. No Bighead Carp, Silver Carp or Black Carp have been observed. In 2013, two triploid sterile Grass Carp were caught in Grand River, a tributary of Lake Erie. In 2014, one triploid Grass Carp was caught in the Grand River. In 2015, six diploid (reproductive) Grass Carp were caught in Lake Ontario and an adjacent pond, and three other triploid or undeterminable ploidy were caught Lake Ontario, Lake Erie and the lower Niagara River. Given the discovery of diploid, or potentially reproductive, Grass Carp in Lake Ontario in 2015, managers need to expand surveillance to include early life stages (fish eggs and larvae).

The issue is to determine the specific time of year to target surveillance efforts for spawning adults and early life stages in high risk tributaries of the Great Lakes so that we can best prevent spawning and control populations. This time window may change from year to year and tributary to tributary. A real-time tool to help field staff determine when to visit high risk areas would be helpful.

Introduction to our product

An application for mobile devices and browsers to quickly check up on the spawning of Asian carp.

How it works

It’s simple, yet intuitive - utilizing the well-known Google Maps as our API we were able to assemble an application that pinpoints the exact spawning locations using real time government data. The severity of the spawn location is determined by the water temperature and water flow rate. These factors are used to calculate the Growing degree-days (GDD) and if the GDD is higher than 650, we can expect the environment to be suitable for carp spawning. The color of the marker indicates the severity. Green marks a safe location with no spawning. Orange denotes moderate spawning (GDD between 650 and 900). Red means the environment is very suitable for mass spawning for Asian carps (GDD above 900).

The application is built on the IBM Bluemix service and utilizes the DashDB add-on for data storage. By using the Ionic mobile framework, we were able to develop a mobile app that complimented the main web version (for Android, iOS and tablets).

What resources are needed for the implementation of this product?

The only resource this product requires is US government data from various stations situated along the lakes and rivers of the North American continent.

http://maps.waterdata.usgs.gov/mapper/

As the above map shows, there are a decent amount of data collection stations throughout the US and Canada (about a few thousand). Our product also provides an API where a user can load in more spawn site markers by entering a station’s unique ID.

What resources are needed for the implementation of the product?

Data input from the water bodies of Asian carp needs to be available for the product to function.

Ways in which it can be implemented

Researchers or anyone can check the map to see if any water bodies meet the criteria for Asian carp spawning. This app will allow researchers to quickly check on the lakes to see if the conditions are met for Asian carp to spawn and to what degree of the size of the spawn should be. By integrating Google Street View, researchers and government teams will be able to survey the nearby aquatic geography virtually. Being more familiar with the geography, experts will know where to set traps and collect data. This will allow them to foresee and prepare for the spawning of the Asian carp. In the end, this will improve operational efficiency.

An application for mobile devices and browsers to quickly check up on the spawning of Asian carp.

How it works?

It’s simple, yet intuitive - utilizing the well-known Google Maps as our API we were able to assemble an application that pinpoints the exact spawning locations using real time government data. The severity of the spawn location is determined by the water temperature and water flow rate. These factors are used to calculate the Growing degree-days (GDD) and if the GDD is higher than 650, we can expect the environment to be suitable for carp spawning. The color of the marker indicates the severity. Green marks a safe location with no spawning. Orange denotes moderate spawning (GDD between 650 and 900). Red means the environment is very suitable for mass spawning for Asian carps (GDD above 900).

The application is built on the IBM Bluemix service and utilizes the DashDB add-on for data storage. By using the Ionic mobile framework, we were able to develop a mobile app that complimented the main web version (for Android, iOS and tablets).

What resources are needed for the implementation of this product?

The only resource this product requires is US government data from various stations situated along the lakes and rivers of the North American continent.

http://maps.waterdata.usgs.gov/mapper/

As the above map shows, there are a decent amount of data collection stations throughout the US and Canada (about a few thousand). Our product also provides an API where a user can load in more spawn site markers by entering a station’s unique ID.

Ways in which it can be implemented.

Researchers or anyone can check the map to see if any water bodies meet the criteria for Asian carp spawning. This app will allow researchers to quickly check on the lakes to see if the conditions are met for Asian carp to spawn and to what degree of the size of the spawn should be. By integrating Google Street View, researchers and government teams will be able to survey the nearby aquatic geography virtually. Being more familiar with the geography, experts will know where to set traps and collect data. This will allow them to foresee and prepare for the spawning of the Asian carp. In the end, this will improve operational efficiency.

Say for example, a hypothetical government committee is tasked with the objective of clearing Asian carp spawning sites near Chicago at Lake Michigan. By using our app, they were now able to locate all the possible spawning sites near the southern portion of the lake. Experts notice a red marker near the Calumet River which indicates possible mass spawning of Asian carps. Knowing the severity of the situation, the local government is able to budget the expenditure by taking in the costs and risks of subduing the location. By using the Google Street View feature, they were able to review the topography and assign the necessary vehicles and equipments to subdue the threat. Due to the commercial use of the river, smaller boats were assigned so they can easily navigate around the larger cargo ships. Many smaller ponds were revealed on Street View too, so teams were assigned to isolate the Asian carps in the ponds for containment. By using our app, not only did the government benefit from the information, but also managed to lower the cost of the entire operation.

Challenges we ran into

One major challenge during the development process was the data storage. We had some trouble with scraping the data from the USGS Waterdata site and putting it into our database (mainly due to data formatting and connections). Fortunately for us, IBM Bluemix experts were on site to guide us through the usage of the Bluemix database service.

What's next for FinTech

Clearly, we built FinTech is scalability in mind. In the future, we want to build a community around our platform with researchers, experts, and fishermen being able to contribute data. Ideally, each marker will pull up more information and perhaps a community discussion. We will also integrate more data features like water pH levels and presence of other species in determining Asian carp spawn sites.

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