Chapters (72)
- TITLE PAGE
- COPYRIGHT PAGE
- DEDICATION
- CONTENTS
- PROLOGUE
- PART I
- CHAPTER 1
- CHAPTER 2
- CHAPTER 3
- CHAPTER 4
- CHAPTER 5
- CHAPTER 6
- CHAPTER 7
- PART II
- CHAPTER 8
- CHAPTER 9
- CHAPTER 10
- CHAPTER 11
- CHAPTER 12
- CHAPTER 13
- CHAPTER 14
- CHAPTER 15
- CHAPTER 16
- CHAPTER 17
- CHAPTER 18
- PART III
- CHAPTER 19
- CHAPTER 20
- CHAPTER 21
- CHAPTER 22
- CHAPTER 23
- CHAPTER 24
- CHAPTER 25
- CHAPTER 26
- CHAPTER 27
- CHAPTER 28
- CHAPTER 29
- CHAPTER 30
- CHAPTER 31
- PART IV
- CHAPTER 32
- CHAPTER 33
- CHAPTER 34
- CHAPTER 35
- CHAPTER 36
- CHAPTER 37
- CHAPTER 38
- CHAPTER 39
- CHAPTER 40
- CHAPTER 41
- PART V
- CHAPTER 42
- CHAPTER 43
- CHAPTER 44
- CHAPTER 45
- CHAPTER 46
- CHAPTER 47
- CHAPTER 48
- CHAPTER 49
- CHAPTER 50
- CHAPTER 51
- CHAPTER 52
- CHAPTER 53
- CHAPTER 54
- CHAPTER 55
- CHAPTER 56
- PART VI
- CHAPTER 57
- CHAPTER 58
- CHAPTER 59
- ACKNOWLEDGMENTS
- ABOUT THE AUTHOR
“Can’t hurt to know where everyone is staying,” said Farrington.
“It’s a block past this next traffic light,” said Gupta. “I’ll run the license plate identification application in live-match mode and see if we pick up any other vehicles from the coffee shop or Whole Foods.”
When activated, the application automatically recorded license plates captured by the Suburban’s cameras, compiling them in a database by time and location filmed, state, and plate number, which they could analyze later. It also ran newly recorded plates through the entire database, looking for matches. The application would allow them to drive through hotel parking lots and identify a vehicle they might have missed while visually surveilling the morning’s other areas of interest.
It also gave them the capability to detect a tail. While driving, they could capture the license plates in front and behind them for a predetermined amount of time. The heavier the traffic, the longer the camera needed to grab all the plates. It would zoom out as far as possible to accomplish this. Thirty minutes later, after executing a few soft evasion techniques—such as slowing down or running a repetitive street-grid pattern—they could reactivate the application with the live-match feature enabled, and identify every vehicle that had stuck with them.
“Scott. Why don’t you climb in back so you don’t get made, just in case they’re having a meetup in the parking lot,” said Farrington.
“Good thinking,” said Daly before leaning his seat back as far as it would go and crawling over it.
Daly returned the seat to its upright position as Farrington turned into the Hilton Garden Inn parking lot. A long driveway passed underneath the hotel’s covered entrance, paralleling the hotel until it opened into the parking lot situated behind the building. He spotted the black Outback immediately, its owner still seated behind the wheel. The man glanced through the driver’s-side window as the Suburban passed but didn’t seem to take interest. Thankfully, the lot was nearly full, the two spaces remaining clearly too tight for his oversize vehicle. He made an attempt to park in one of them, lining up a few times before driving away, to demonstrate to the Outback’s driver that he’d tried.
“Was he watching me the whole time?” asked Farrington.
“No. He went back to looking at his phone as soon as you passed by,” said Gupta. “Looked up once after that, but just for a moment.”
“Thank god the lot was full,” said Farrington. “I wasn’t expecting it to be this small, with one way in or out.”
“That’s my fault,” said Gupta. “It looked like it connected to the street behind it on Google Maps, or I would have said something.”
“Any hits on any other vehicles?” asked Farrington. “I didn’t see the Durango or Pathfinder.”