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Flow Lab

The Forest Flows programme will focus on developing methods to predict and optimise water use and supply in planted forests to answer the questions: Where is the water? Where is it going? And who gets to use it?​​

Using novel technology this programme allows the team to develop a hydrology model on five sites across New Zealand, from data collected on water use, storage and movement, at tree, stand and forest scales. The remote sensing devices includes over 600 dendrometers (tree growth sensors), 200 soil moisture sensors, nitrate sensors and a P-band radar that uses microwaves to penetrate the ground and measure variation in soil moisture levels. ​​

Scion approached inFact to develop the dendrometers, dataloggers and local wireless network and base stations required for capturing real-time data on-site and relaying this via 3G to a cloud backend.

Ruggedised low power long-life wireless sensor and datalogger network ​

Flow Lab

by Scion
Flow Lab

Now we want a better understanding of how much rainfall is stored within a forest and to what degree it is released, ... Our aim is to protect primary sector productivity at the same time as improving water quality and allowing for future urban and rural demands for water.

Programme leader Dean Meason // Scion // APR 2020

The Project

The project team works side-by-side with the client to ensure product functionality, marketability and usability are resolved through proof of concept prototypes. These are tested and refined to ensure all aspects of the solution are understood, key risks are identified and project goals are achieved.


The challenge was creating a highly resilient low power mesh network capable of being deployed into dense forests and steep gullies whilst operating without packet data loss from the datalogger nodes to the base station. ​​

inFact brought together its team of specialist RF, wireless and industrial engineers to define a mesh network that could route data from one node to the next finding the optimal pathway back to the base station without the inherent fallibility of a daisy chain approach. ​

Diagnostics and OTA configuration and firmware updates are made possible remotely using inFact’s extensive knowledge and experience. ​


Scion chose inFact because of its extensive experience in ultra-ruggedised low power sensing and wireless network systems. For less than the cost of off the shelf dataloggers Scion could specify and build a customised system that could handle 5 years in the extreme environments of New Zealand forests.​​

inFact developed a specification in collaboration with the science team and kicked off the project just prior to COVID-19.​


Scion is deploying systems across the country that will operate for five years with minimal human intervention or required site visits. Multi-levels of redundancy are built into the systems to ensure data integrity.​​

The flow of information from the systems deployed across the country allows the science team to access and analyse data in real-time and respond rapidly.​

Capabilities used on this project

Cloud Services

App Development


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