top of page
Artboard – new-q-q.png


Talking the same language


Blockchain GS1-EPC global

Industry 4.0 Internet of

Things (more)


Because RF-sensing and the Internet of Things are so new, it’s common that terminology and concepts are unfamiliar. Below is Infratab’s collection of terms and references, organized by our areas of interest, which we'd like to share with you.


Radio frequency Sensors

Edge computing Cloud



Because RF-sensing and the Internet of Things are so new, it’s rare that any of us know all the terminology used. Below is Infratab’s collection of terms and references, organized by our areas of interest, which we’d like to share with you


Internet of Things


Real-time shelf life:

  • Real-time alerts by life-used by business processes or by life-left,

  • Live dates: ship-by,receive-by, sell-by


Real-time shelf life:

  • Change in perishable handlers’ perspective from “no problem on my watch” to “here’s where we can reduce


Real-time shelf life: 

  • Real-time alerts by life-used by business processes or by life-left,

  • Live dates: ship-by, receive-by, sell-by, best-when, use-by,

  • Supplier score cards that include shelf life,

  • First expired-first out, FEFO), Inventory mgt,

  • Condition-based blockchain events

  • Cold chain packaging performance analysis,

  • Live date "perishables labels" 

  • Life starts at 100; ends at 0

Real-time shelf life

Infratab Freshtime products perform traditional sensing operations, and at the same time, can monitor and calculate shelf life-used and left of a tagged item.

Shelf life can be calculated in-tag, in edge software that reads tags, or in the cloud. When shelf life is calculated in-tag, Infratab calls the label, a live date label

Although many different shelf life algorithms (models)can be used, Infratab’s preference is Freshtime Points. Freshtime Points is based upon a simple concept: a perishable’s life starts at 100 at birth and ends at 0 at its Use-By (quality end of life) date.

y combining an item’s spoilage algorithm, with the sensing interval set in-tag, Points-Used, and Points-Left can be calculated each time temperature is sensed. Both Points-Used and Left can then be converted into the number of hours used and left for the sensing interval. (see RF-Sensor Solutions).


Real-time shelf life: 

  • Change in perishable handlers’ perspective from “no problem on my watch” to “here where we can reduce shelf life loss”

  • Freshness pricing,

  • Analytics

  • AI (Artificial Intelligence),

  • Comaprisions

  • Ranges (bands),

  • Predictions,

  • Freshness pricing,


2-module tag design:

  • Temperature sensor separate from RF for higher accuracy,

  • Long or clip tags: RF, display, and battery on outside of box; sensor inside the box

  • Multiple sensors,

Tag with SoC RF-sensor:

  • Small footprint tag,

  • One  sensor in RF chip.

  • RF-sensor System-on-Chip

  • “Lego-like” RF-sensor tags

Piggyback sensor to RF

Piggyback sensor to RF•“Lego-like” RF-sensor tags•RF-sensor System-on-Chip Infratab was started with the idea of a “live-date label—consisting of an off-the-shelf, GS1 supply chain RF chip and antenna and a digital sensor (piggyback).

The innovation: use RFID chip memory as the router or depository of sensor data between RFID reader and sensor. The benefit: standard off-the-shelf RFID readers could be used to read and write sensor data. It worked!

More ideas followed:

  • Serial Interface, (I C or SPI) for performance,

  • In-tag database and business  vocabularies,

  • Business event tracking of temperature and shelf life,

  • Data security by brand owner, partner or public

  • Long tags for aluminum-lined shipping containers.

  • Dual RAIN-NFC tags for widespread use

Best, RF chip manufacturers endorsed the architecture and combined RF chip and digital sensor circuitry into System-on-Chips (SoC). The result: a selection of RF-sensor enabled chips (RAIN, NFC, BLE, LoRa, Sigfox), able to run Freshtime tag software. (see Freshtime Inside).


2-module tag design

  • Temperature accuracy

  • Product, not ambient, temperature monitored,

  • Connectible sensors,

  • Multiple sensors,

  • User can use NFC, display, QR, or barcode without opening the box

Tag with SoC RF-sensor:

  • Small footprint tag,

  • Best uses items, spaces(location), GS1 SSCC(shipping container), and consumer RF tags,

  • Selected chips:battery less temperature reading (snapshot),

  • Low cost tags



  • Sensor status and history continue from parent to child,

  • Multiple RF air frequencies in one tag,

  • Transfer status to RF-sensor, RFID, barcode, or printed label by RF reader or directly



Infratab Freshtime’s inheritance feature is used when product bundles, (pallet-case-item), are separated or a bulk container of liquid is subsequently bottled or cased(wine, beer, milk).

Inheritance enables sensor status and history to be transferred from an RF-sensor device (parent) to a child. The child can be another RF-sensor tag, an RF-transponder chip or tag, or a printed label

The communication link used in the data transfer from parent to child can be either an RF reader or a direct connect from the parent to child.

Infratab’s dual RF frequency RF-sensor tags are examples of the direct connect. At each sensing interval, sensor status is sent from sensor to the parent RF transponder memory and then to Rf child transponder. (see Freshtime inside).


Inheritance via RF reader:

  • An RF-sensor label with sensor setup, status and/or history continues when pallet is broken up,,

  • When child tag is a printed label, color scan be used for status,

Inheritance via direct communication:

  • A multi-RF tag in which status in RF parent and child transponders are the same.


perishables Items:

  • Perishables, refrigerated but removed from refrigeration for short periods of time:

  • Research labs: enzymes, biomarkers,

  • Aerospace service departments: adhesives, sealants,

  • Spas: cosmetics

  • Multi-sensor shelves,totes, cosmetic cases or pallet liners

  • Infer shelf life: time left out of to time returned to the monitored area.



There are situations in which items are removed from a monitored environment for a short or defined period of time. The temperature outside is near-constant.

An example situation is a university research lab where enzymes are refrigerated and monitored. When these items are removed by researchers, the times out and the times returned are logged—often using paper and pencil. The challenge occurs when items remain out of the refrigerator for longer than allowed or logging is forgotten. Experiments are at risk. There is confusion about whether items should be tossed

Infratab Freshtime’s Inference shelf life model, estimate the shelf life used while the item is away from a monitored environment.


Perishable items whose price point is too low for RF-sensor:

  • Automatic compliance reports for the time a perishable is away from a monitored environment,

  • Less toss: Inferred shelf life left at return, indicates which items should be used first,

  • Live tracking, notifications by the monitored environment when item out of refrigerated environment too long,

About Infratab Freshtime

Infratab Freshtime: Stepping into the future

Internet of Things (IoT)

Identify: get info about an item

Sense: know its condition

Notify: provide info to those


Analyze: gain insight

Share: include others in what happened

Introducing Infratab Freshtime

Infratab Freshtime uses RF-sensors to collect data about the condition of things. Smartly. Simply. Timely

The Infratab Freshtime product line brings you into the world of IoT:

     item identification, sensing, condition monitoring, real-time edge and cloud computing, analytics, artificial intelligence           (AI), data exchange, blockchain, and more. Today. Painlessly

Freshtime is GS1 supply chain savvy. A Freshtime tag’s ID is a GS1 ID, called an EPC. Freshtime tags are used, side-by-side with GS1 QR & barcode labels. They know and use GS1 data. The is used with GS1 RF readers

For users, including consumers, who know nothing about GS1-no Problem. Freshtime is for you too. 

Condition Intelligence

Modal: get info about an item

mathematical description of spoilage characteristics of an item

Alert: signal when the actual event does not meet a specific condition

Predict: using the model and current data, estimate a future event

bottom of page