The Data Payload

This chapter examines what flows through the connectivity pipe — and where that processing runs: on the device, in the cloud, or at an emerging hub tier in between. Through first-person case studies in patient monitoring, warehouse AI, and fleet management, it traces the progression from raw telemetry to autonomous fleets, and shows why the ratio of humans to devices is the economic metric that matters most.

Chapter 8 was about the connectivity pipe. This chapter examines the data payload filling it, and its possible endpoints. As tangibles evolve from standalone devices to managed fleets, the scope of data they generate expands – from simple status indicators to rich sensor streams, from raw telemetry to actionable intelligence. At each step, the value of the connection grows: a device that only blinks error status is just a little more than a black box. A device that senses its environment, interprets what it finds, and acts on it becomes a different product entirely. The value of these data transfers increases in the physical world, too, as the need for on-site attendance is gradually eliminated.

Take EyeClick’s EyeWiz. Originally an interactive projector that could turn any floor into a playground. Children stomped on virtual butterflies, kicked projected soccer balls, splashed through digital puddles. The hardware was impressive – a ceiling-mounted projector with a 3D camera tracking movement in real time. And it was connected, too: it accepted firmware updates over the air and its logs could be queried from a remote control console.