InPlay Expands Collaboration with Hubble Network for Global Smart Labels

May 6, 2026
InPlay Inc. has expanded its partnership with Hubble Network to develop IN120-based smart labels and wireless sensors with global connectivity across terrestrial and satellite networks.
InPlay Expands Collaboration with Hubble Network for Global Smart Labels

InPlay Inc. has expanded its partnership with Hubble Network to introduce IN120-based smart labels and wireless sensors capable of global tracking through both terrestrial and satellite infrastructure, announced in a press release.

The collaboration builds on earlier work combining InPlay's NanoBeacon technology with Hubble's satellite-enabled Bluetooth network. The new IN120 platform adds patent-pending data logging that continuously records sensor data, enabling time-sequenced monitoring for applications such as cold chain logistics and asset tracking.

The IN120 features a minimalist design requiring only one external component, which reduces system complexity and manufacturing cost. It supports ultra-low power operation and can function with thin batteries or energy harvesting, allowing for maintenance-free deployments.

The joint solution provides hybrid connectivity through Hubble's network of over 95 million gateways and satellites, delivering continuous asset visibility without dedicated infrastructure or cellular service. Target applications include pharmaceutical monitoring, smart packaging, industrial condition monitoring, and remote asset management.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Enterprise AI Brief, Industrial AI Weekly or Daily AI Brief.

Also, consider following us on social media:

Free newsletter

Enterprise AI Brief

Weekly report on AI business applications, enterprise software releases, automation tools, and industry implementations.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.