Our foray into IOT has a running start with Daniel Bradby (CTO Eliiza & Mantel Group) and Brett Henderson (CTO DigIO) having a background in electronics engineering on top of extensive experience in software development, data engineering and artificial intelligence. We have the skills and the appetite to learn, but needed the right use case. It didn’t take long to come up with something that got the team excited, or at least me ! I have been making wine for the last 7 years and lease a vineyard, this passion provided the perfect opportunity to leverage technology advancements and implement an IOT Vineyard and Winery. The promise of plenty of field trips got the rest of the team on-board, you should never underestimate self interest !
VInOT is the working title for our project which will combine team members from both DigIO and Eliiza. We are looking to use VInOT to demonstrate the technical feasibility of current IOT technology, its viability from an economical perspective and the desirability of outcomes that can be delivered to grape growers and winemakers. We expect to leverage these outcomes across other industry segments in the future.
The following are the key objectives we want to demonstrate over the coming months:
- Use of sensor networks to collect data
- An initial focus will be on soil moisture of grape vines at varying depths, with the inclusion of additional atmospheric information such as sunlight, humidity, precipitation and wind over time.
- Deploy and manage IoT sensors in the field
- Demonstrate both manual and over the air software deployments to IOT devices that leverage the Amazon Web Services (AWS) IOT Services suite, as well as the resilience and reliability of devices and networks such as LoRaWAN.
- Apply analytics/AI to make decisions.
- Creation of dashboards and data displays that support manual decision making, with the development of learning algorithms to automate decision making. i.e. Based on the amount of sunlight, current humidity and temperature there may be an alert to watch for powdery mildew on the vines.
- Automatically/remotely control systems.
- Demonstrate the automation of vineyard activities such as watering based on the sensor data
- Extending beyond sensors
- Demonstrate the use of Computer Vision and Image Recognition to provide crop estimates and identify disease
We look forward to sharing our VInOT experiences over the coming months through our blog posts.