Nevada start-up Dot Ai has launched IoT hardware to improve asset tracking in logistics and supply chain management.

The patented ZiM (zero infrastructure mesh) technology was developed by people from the RFID and IT security industries to replace the outdated and expensive technologies logistics operations have relied on for decades.

“After years of meticulous research and development, we are launching our revolutionary ZiM IoT technology in the market,” said Dot Ai (daic.ai) CEO Edmund Nabrotzky. “We believe this first-of-its kind technology will transform the landscape of asset tracking for logistics, an industry that relies heavily on manual processes as well as RFID technology, which has not seen major innovation since its conception in the 1980s.”

ZiM is designed to offer asset management by securely gathering data at the edge of the enterprise. It can read both passive (battery free transponders) and active (battery powered beacons) to provide data for supervisory systems. The bridge can operate with its own battery power when mounted on moving racks or pallets or be hardwired to power for fixed installation in aisles or doorways.

Up to four general purpose IO pins are available to connect the bridge to external sensors or signalling devices to enhance workflows. It also has integrated bright signalling LEDs to direct workers in common tasks.

Legacy systems rely heavily on personnel to execute orders and workflows, only collecting data at the start and end of significant process milestones. The ZiM hardware can be present and move through the process as an IoT edge offering, enabling real-time and constant data collection throughout. This approach is critical in providing a rich source of data for optimisation of AI integrations, including the AI engine developed by Dot Ai.

AI camera integration is also available in this engine, enabling object recognition and image and video capture in the asset record as an overlay to process data collected wirelessly by ZiM.

Dot Ai SaaS software leverages the tools of agile cloud services, including a rules engine to define and enforce application-specific behaviour. The engine can constrain, monitor, alert or drive device actions to prevent rule violations, increasing efficiency through common machine-learning techniques. Another use of AI is to enhance common material handling workflows by providing real-time, context-aware suggestions and actions based on intelligent algorithms and learned enterprise-specific workflows.

Full-scale production and deployment of ZiM technology is set for the end of this month.