IoT live tracking with ASPION L-Track:
Transport monitoring in all dimensions.

Asset tracker for secure supply chain

The new IoT transport data logger ASPION L-Track monitors your transports worldwide – in real time with 360 degree live tracking. The connected Internet of Things (IoT) platform provides round-the-clock access to the current location and condition of goods and immediately informs in case of unusual incidents. This makes the current transport loads and environmental conditions for high-value transport goods transparent, traceable and assignable at all times – especially in the event of damage.

The various components interact to provide an integrated end-to-end solution for live transport monitoring “made in Germany”.

The advantages at a glance

Live-Data

Recorded data are transmitted via mobile radio worldwide and in real time and can be retrieved at any time.

Worldwide

Can be used in over 140 countries worldwide, thanks to mobile communications with LTE-M and 2G as fallback.

Reliable

All data is reliably logged in the ring buffer until the next transmission, even without a mobile radio signal.

Versatile

A wide variety of influencing variables such as shocks / impacts, temperature, humidity,… and more, as required.

Durable

Highly robust ABS housing with IP65 protection and replaceable batteries for multi-year, resource-saving use.

Ergonomic

Ergonomic cloud platform, easy-to-create reports and meaningful evaluations – for satisfied users.

Simple

Simple activation and initialization in just a few steps directly on the transported goods.

No labeling obligation

Not subject to labeling requirements thanks to alkaline batteries – universally applicable across all industries for many scenarios.

Made in Germany

Completely Developed and manufactured in Germany.

Application areas: 360 degree live tracking

The new ASPION L-Track – just like its predecessors in the ASPION G-Log series – has been specially developed for monitoring high-value and sensitive transport goods. Particularly for manufacturers in the mechanical and plant engineering, automotive and electronics industries, energy sector as well as logistics and packaging industry, the IoT asset trackers collect valuable information and provide real-time updates about the location and condition of the goods. Damaging transport loads and environmental impacts are reported and visible immediately after they occur. Thus, unforeseen events can already be reacted to during transport and potential damage can be averted. Due to its energy-optimized mode of operation, the ASPION L-Track is particularly suitable for asset tracking with multi-year durations for goods deliveries and in warehouse logistics. This guarantees transparency and security in your supply chain – anytime, worldwide and long term.

How the ASPION L-Track works

The ASPION L-Track is attached directly to the transported goods and can be activated in just a few steps. During the entire transport route, it logs and transmits all events that occur: Position data, shocks and impacts, temperature and humidity values, air pressure and other measured values. The transmission of sensor data to the ASPION Cloud IoT platform is interval-based via mobile communications and works in more than 140 countries worldwide thanks to LTE-M and 2G as fallback. In the ASPION Cloud, the sensor data can be viewed at any time and threshold values can be set and changed, even during transport.

ASPION Cloud IoT Platform: Easy data evaluation in real time

With the ASPION Cloud, a powerful web-based IoT platform, location and sensor data of the L-Track devices can be easily displayed and evaluated. The platform provides around-the-clock access to the current location and status of the IoT trackers, keeping users informed of the status of their delivery at all times. In addition, alarms and thresholds can be set to be notified immediately of any unusual occurrences. Groups can be used to sort devices by different deliveries, locations or departments. Intuitive dashboards help to quickly and easily analyze sensor data and draw meaningful conclusions.