ATLAS Network

With the goal of this challenge being to create a commercializable prototype that demonstrates accurate indoor localization within 1 meter of accuracy that is also easy to deploy, we wanted to understand this space and existing solutions. We conducted various interviews as part of our research and plan on continuing this practice. With all this information, we have created the ATLAS Network. This system uses a sensor fusion methodology that uses both IMU data and Low Energy Bluetooth information to perform in-door localization. We plan on implementing the Personal Dead-Reckoning system that has been heavily implemented in research. To further improve accuracy, we plan on mapping a mesh network using the deployed devices as both the Bluetooth transmitter and receivers among themselves. This data will then be sent via Bluetooth to a console hub positioned outside. At this hub, this data will be visualized and backed up on an Amazon Web Services (AWS) server for future analysis and reflection. The sensor suite itself will be protected by a heat and shock resistant casing to ensure proper functionality during rescue operations.   We believe that ATLAS Network will find more success than the current commercial technologies using IMU technologies because of our novel mesh network in addition with recent advancements in the related software aspects of this field. Additionally, other technologies that provide much more significant accuracy within this problem space require a complex and time intensive set up or will not work well in situations where the environment is different than what it is intended for. This is a significant hurdle, and we recognize that it will be unlikely for any technology to be adopted by our customers, firefighters, if this is the case.   The following is what we would expect an operation using the ATLAS Network to look like. Once the first responders arrive on site, they simply set up the console hub and start up the program. As each firefighter enters the building their sensor is calibrated to their starting position. This can be done either by the firefighter or the controller who is coordinating the effort. Once that step is done, there is minimal effort required by either party: the firefighter and the controller outside. The information from the firefighter’s sensor suit will be communicated back to the console hub outside. This will then provide a visualization on site as well later back up this information to a secure cloud server. Should a firefighter become immobilized, the controller can then direct the other responders to the injured individuals via the info on their console hub.   As we move forward with this project, we hope to meet with like-minded individuals in developing a robust solution to aiding emergency responders battle dangerous situations.

Basics

  • Number of Employees
    0-1 employees
  • Stage
    Full Product Ready
  • Founded
    2019
  • Primary Industry

Description

With the goal of this challenge being to create a commercializable prototype that demonstrates accurate indoor localization within 1 meter of accuracy that is also easy to deploy, we wanted to understand this space and existing solutions. We conducted various interviews as part of our research and plan on continuing this practice. With all this information, we have created the ATLAS Network. This system uses a sensor fusion methodology that uses both IMU data and Low Energy Bluetooth information to perform in-door localization. We plan on implementing the Personal Dead-Reckoning system that has been heavily implemented in research. To further improve accuracy, we plan on mapping a mesh network using the deployed devices as both the Bluetooth transmitter and receivers among themselves. This data will then be sent via Bluetooth to a console hub positioned outside. At this hub, this data will be visualized and backed up on an Amazon Web Services (AWS) server for future analysis and reflection. The sensor suite itself will be protected by a heat and shock resistant casing to ensure proper functionality during rescue operations.
 
We believe that ATLAS Network will find more success than the current commercial technologies using IMU technologies because of our novel mesh network in addition with recent advancements in the related software aspects of this field. Additionally, other technologies that provide much more significant accuracy within this problem space require a complex and time intensive set up or will not work well in situations where the environment is different than what it is intended for. This is a significant hurdle, and we recognize that it will be unlikely for any technology to be adopted by our customers, firefighters, if this is the case.
 
The following is what we would expect an operation using the ATLAS Network to look like. Once the first responders arrive on site, they simply set up the console hub and start up the program. As each firefighter enters the building their sensor is calibrated to their starting position. This can be done either by the firefighter or the controller who is coordinating the effort. Once that step is done, there is minimal effort required by either party: the firefighter and the controller outside. The information from the firefighter’s sensor suit will be communicated back to the console hub outside. This will then provide a visualization on site as well later back up this information to a secure cloud server. Should a firefighter become immobilized, the controller can then direct the other responders to the injured individuals via the info on their console hub.
 
As we move forward with this project, we hope to meet with like-minded individuals in developing a robust solution to aiding emergency responders battle dangerous situations.