Indoor Localization System

Updates on
Indoor Localization System
Kaifei Chen, Siyuan Jack He, Randy Katz, David Culler
Old System Design
In old system, application collects data from sensors and
sends requests to localization server
• It becomes throughput bottleneck
• It becomes functionality bottleneck (deal with
different sensors and algorithms)
A sensor/algorithm can be used by several components
System breaks if any components doesn’t conform to
data structure
New System Design
System Dataflow
Acoustic Ranging Using De-convolution
WiFi Fingerprinting
WiFi Signal Strengths Are Not Stable
WiFi Appearance Possibility Are Stable
• Use Message Queue as Overlay Network
• Mobility, caching, multicast, security
• Separate Sensor, Algorithm, and Users
• Sensors are deployed by their owner. They publish to
their own topics.
• Algorithms are instantiated by and talk to our Golang
wrapper via Cap’n Proto. They define their input and
output data schema.
• Users instantiate algorithm by publishing input and
output topics to an algorithm wrapper.
• Broker verifies data schema on each topic
Signal Strengths Result, 69% Accuracy
Appearance Possibility Result, 88% Accuracy
• Send Sine Sweep Wave f(t), and
denote its time reversal as f’(t)
• Record acoustic response g(t)
• Get impulse response
y(t) = g(t) * f’(t)
• Find peaks in y(t) and calculate