
Datasmart TRACK
Self-powered Asset Tracking
M2M Datasmart offers a variety of tracking devices for monitoring location, acceleration, temperature, humidity and light. These can be attached to a product, package or transport vehicle. IP-67 rated for dust and water penetration, application examples include cannabis, sensitive food types, refrigerated transport or just knowing where your truck is!
M2M Datasmart, Inc. is pleased to now offer a revolutionary new asset tracker from Suntech USA.
The 4910 Series is half the cost and features a military-grade battery with twice the battery life vs. competitive trackers. In fact, at three pings/day, you may never need to replace the battery - it lasts over 10 years!
The 4910 is easy-to-mount, ruggedized in a grey enclosure, waterproof, dust-proof, accurate to within 3 meters, and includes a 3-axis accelerometer
Key Features:
LTE Cat-M1/NB-Io
Lithium Thionyl replaceable Battery
Extremely low power consumption
Low Battery Alert
Built-in 3-axis accelerometer
Firmware upgradeable remotely (OTA)
Waterproof IP67 Compliant
Options:
(Coming Soon)
Wi-Fi Geolocation
Temperature and humidity detector
Barometric pressure sensor
Maintenance server supported
BLE
Advantages:
Tightly integrated edge-to-enterprise solution
LTE-M / NB-IoT, with 2G fallback
Monitors location, motion, temperature, and humidity
Industry-leading battery performance
Highly configurable to your use case
NL-AT2
AT2 is a versatile, ruggedized asset-tracking device that leverages cellular, GPS, Wi-Fi, and environmental sensors to deliver solid reliability for monitoring location, motion, temperature and humidity. The AT2 device is IP-67 rated for water and dust resistance, works indoors and out and carries a robust power management system delivering exceptional battery life. This asset tracking devices also supports multiple frequency bands and is globally capable
IP-67 water and dust resistant
Drop resistant to six feet
Globally capable – Multi-band support
Enterprise integration – RESTful API / PubSub
Flexible business models