Luke Hull UAS Geospatial Applications

Experiment Updates & Paper Introduction Experiment Updates Since our last blog post, we have ran quite a few different tests over two different data sets. At this time, we are very much in the proof-of-concept stage in regards to Loc8's usage. However, we seem to be proving that it is a very viable alternative to traditional methods, and in some cases, will be much more efficient. Our tests utilized a few different methods for using Loc8 as we are still dialing in the best way to use the software to achieve the best results. Below I will describe the different experiments we have run so far, and our preliminary results and discussion about the software. DJI Mavic 2 Pro Testing We acquired data for three different flights, as outlined in our previous post. Since then we have tested some of this data in Loc8, and had surprisingly decent results. Our flights started by taking images of the clothing with a phone camera as a baseline for Loc8 to go off of as far as color va

ArcGIS Story Map We created an ArcGIS story map to help document our research project and display our field work and goals in a user friendly interactive way. This story map will grow and change with us as we progress in our research, it will show how we will accomplish efficient search and rescue with unmanned aerial vehicles. The current story map gives an outline of how we will accomplish what our goals are, outlining our experiments and field work. When we have more experiments completed and more field work we can create maps and also interactive maps of where our field sites are located. We can also display an individual field site map and show where an individual was located from our experiment. Click on the image below to view our UAV Search and Rescue Story Map.

Field Work Friday September 6th, 2019 This was our first day of field work and collecting data to use in Loc8, 3 flights were flown over the Purdue Wildlife Area. The flights were designed to portray a search and rescue mission. Prior to the flight we have taken “last seen” pictures of a team member to act as a missing person. The clothes that were worn in those pictures were then placed randomly in the field. Each flight was flown with similar parameters besides overlap. We are now testing to see how overlap will affect our data and if Loc8 will have any problems identifying the objects.  Figure 1: Experiment Details This experiment used a Mavic 2 Pro and the clothes set out in the field were all of different colors to test how darker or brighter colors will be identified. Total flight times were recorded to test which method is the fastest and compare a normal search and rescue mission with a search and rescue mission using UAV’s. Times were also noted

Digging Into your Projects: How to Ask the Right Question of what needs to be done and what needs to be learned Description: There have been several ways in which humans have carried out Search and Rescue (SAR) operations. Conventionally it has been with manned aviation, or with foot searchers, or some combination thereof. More recently with the advancement in Unmanned Aerial Systems (UAS) and the associated technology, UAS platforms have been utilized in SAR operations, both because of the reduced operating cost, and because of the sensors these platforms can carry. One main difficulty with UAS operations in SAR missions is the volume of data that can be collected with UAS platforms. This requires time to sift through, and even still, there needs a better way to sift through the images than to have humans do the work, because humans will miss something. Loc8 is a desktop application that processes images by searching for individual, or groupings of specific