When a hydroponic crop grows, manual dexterity becomes the first bottleneck.
Automation is not about "making the system smart": it is about making it stable, replicable and scalable.
In this article we analyze the three pillars of hydroponic automation-pumps, valves, and controllers-clarifying what they really do, what mistakes to avoid, and why without proper architecture even the best AI is useless.
Automating means taking human variability out of critical parameters:
water flows
irrigation timing
oxygenation
recirculation and drainage
rapid reactions to abnormal conditions
The real benefit is not the time savings, but the repeatability of the crop cycle.
Without automation, each cycle is slightly different from the previous one. With automation, cycles become comparable. And therefore improvable.
Submersible pumps
inexpensive
easy to install
suitable for small or domestic systems
Limitations: poor accuracy and limited service life
External / centrifugal pumps
more stable flow rate
longer service life
ideal for medium to large systems
Require proper hydraulic design
Peristaltic pumps
extremely accurate metering
critical for nutrients and pH correctors
low flow rate, high control
Choosing a pump based only on gallons/hour.
In reality, they also count:
actual head
continuity of operation
compatibility with the control system
Valves decide where and when water (or air) flows through.
On/off valves
simple
robust
binary (open/closed)
Proportional valves
modulate flow
fundamental in advanced systems
allow dynamic micro-adjustments
In a multilayer or multi-crop system, valves are what allow each line to be treated as an independent micro-system.
Automating the pumps but leaving the valves manual.
Result: a "half-automated" system that is rigid and not scalable.
The controller is the brain that:
reads the sensors
decides what to do
activates pumps and valves
records data
Timer
no feedback
apparent automation
zero adaptivity
PLCs/microcontrollers
conditional logic
industrial reliability
basis for serious systems
Software control + cloud
dynamic logics
historical analysis
AI integration
remote management
This is where the real paradigm shift occurs:
the system no longer just executes instructions, but reacts to the context.
An automated system that does not record data
does not improve
does not scale
does not learn
Every actuation (pump turned on, valve opened, dosage made) must become structured data.
Only then is it possible to:
compare cycles
identify inefficiencies
build predictive models
introduce AI in a meaningful way
In the Tomato+ system, automation is not an adjunct, but a basic condition:
pumps and valves designed to work with software logic
controllers integrated with sensors and cloud
continuous feedback loop between plant and artificial intelligence
possibility to treat each crop as a specific case
This allows:
production stability
dramatic reduction of errors
replicability on a large scale
continuous learning of the system
It is not just automation: it is growth infrastructure.
Pumps, valves, and controllers are not separate technical components.
They are a single distributed decision-making system.
Those who think of them as "hardware" miss the point.
Those who design them as part of a data-driven ecosystem build a real competitive advantage.
Thank you for reading this article. Keep following us to discover new content on hydroponics, vertical farming, and smart agriculture.
Tomato+ Team