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A LoRaWAN greenhouse monitoring system connects distributed sensors to a gateway, then sends their readings to a network server and dashboard. It is well suited to low-power, battery-operated monitoring across greenhouse zones; it is not a substitute for local safety controls on heaters, pumps, vents or other equipment. For most multi-sensor installations, LoRaWAN is the relevant term: LoRa is the radio technology, while LoRaWAN defines how devices communicate across the network.
How a LoRaWAN greenhouse system works
Sensor nodes measure conditions and send small wireless messages called uplinks. A gateway receives those messages and forwards them over Ethernet, Wi-Fi or cellular backhaul to a LoRaWAN network server. An application then decodes, stores and displays the data, raises alerts, or passes selected information to a controller.
LoRaWAN is a low-power wide-area protocol built on LoRa radio technology, and gateways bridge device traffic to network services. AWS explains the relationship between LoRa and LoRaWAN. A typical route is:
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#1 Best Overall
- Dragino DR-SE-6P - Soil Moisture Sensor Probe
- The DR-SE-6P is a Soil Moisture and EC Probe
- This Probe can be used with the Dragino SE0X-LB – LoRaWAN Soil Moisture & EC Sensor Transmitter
- LTC2-LB supports BLE configure and wireless OTA update which make user easy to use
- Accessories, Smart Agriculture
| Term | Meaning |
|---|---|
| LoRa | Radio modulation and physical-layer technology. |
| LoRaWAN | Network protocol for device communication, addressing and security. |
| End device | A sensor or actuator node that communicates over LoRaWAN. |
| Gateway | A radio bridge that receives device messages and forwards them to the network server. |
| Network server | Authenticates devices, manages network traffic and routes messages. |
| Application | Decodes and uses data for charts, alerts, storage or automation. |
| Uplink / downlink | An uplink goes from a device to the network; a downlink goes from the network to a device. |
A point-to-point LoRa link can suit a small custom project, but the builder must provide more of the device management, security, retry and scaling logic. For a multi-sensor deployment, LoRaWAN usually offers a more complete network framework.
When LoRaWAN fits—and when it does not
LoRaWAN is a strong candidate when sensors are spread across greenhouse bays or nearby irrigation areas, battery operation matters, and readings are periodic rather than continuous high-volume data. One gateway can receive messages from many nodes, and sensor locations do not each need Wi-Fi coverage or data cabling.
- Good fit: temperature and humidity monitoring, root-zone moisture readings, tank levels, equipment-state messages and threshold alerts.
- Poor fit: video, images, large files, or control loops that need consistently fast, frequent communication.
- Use caution: metal framing, reflective insulation, water, dense crops and enclosed bays can affect radio performance. Test signal quality at actual sensor positions; a generic range claim is not a deployment guarantee.
Battery life and delivery reliability depend on factors including reporting frequency, payload size, radio conditions and device configuration. LoRaWAN is primarily designed for uplink telemetry, so frequent downlinks can consume battery and network capacity. For that reason, use it to monitor and issue occasional commands rather than to carry a fast, safety-critical control loop.
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Choose measurements for decisions
Start with the operational decisions the system needs to support. A sensor is useful when its reading helps an operator change irrigation, ventilation, shading, enrichment or maintenance—not simply because the device can measure another variable.
Air temperature, humidity and VPD
Measure temperature and relative humidity at representative crop height, not against a wall or beside a heater, cooling pad or vent unless that location is being monitored intentionally. In a large greenhouse, use separate readings for zones that differ in crop, exposure or climate equipment.
Relative humidity alone can be misleading because the same percentage at different temperatures represents different moisture conditions. A dashboard can calculate vapor-pressure deficit (VPD) from temperature and humidity. VPD is a useful indicator for interpreting plant moisture stress, but there is no universal target: crop, growth stage, lighting, irrigation and cultivation practice all matter.
Rank #2
- D22-LB LoRaWAN Waterproof /Outdoor Temperature Sensor
- D22-LB LoRaWAN Waterproof /Outdoor Temperature SensorThe Dragino D22-LB is a LoRaWAN Temperature Sensor for Internet of Things solution
- D22-LB will convert the Temperature reading to LoRaWAN wireless data and send to IoT platform via LoRaWAN gateway
- The LoRa wireless technology used in D22-LB allows device to send data and reach extremely long ranges at low data-rates
- LoRa / LoRaWAN, Sensors, Temperature & Humidity
CO₂
CO₂ monitoring can support ambient-condition tracking, enrichment management and assessment of ventilation-related losses. Place the sensor to represent the crop zone, away from direct gas discharge, strong air jets and condensation. CO₂ devices may use more power and require more maintenance than basic temperature-and-humidity nodes. Enrichment settings and safety procedures should come from crop-specific guidance and the greenhouse’s gas-management practices, not a general-purpose sensor article.
Light and PAR
For plant-light decisions, distinguish a general illuminance reading from PAR or PPFD-oriented measurement; lux is not interchangeable with PPFD. A suitable sensor can help track light at the crop plane, shade-screen effects, supplemental lighting and daily light integral. Install it level and unobstructed at the relevant measurement height.
Soil or substrate moisture and EC
Moisture readings are meaningful only in context. Sensor type, substrate, probe depth, container geometry, irrigation method and position relative to emitters all affect interpretation. Place probes in representative root zones, and test them in the actual growing medium. A reading beside a dripper may reflect the emitter plume rather than conditions throughout the root zone.
Electrical conductivity (EC) can help indicate nutrient concentration in soil solution or hydroponic systems, but probes require suitable installation, cleaning, temperature compensation and interpretation. A low-cost probe should not be assumed equivalent to a commercial agricultural or hydroponic instrument.
The The Things Network device repository’s moisture category includes LoRaWAN devices that measure combinations of moisture, temperature and EC. Device availability does not remove the need to verify calibration and suitability for the particular substrate.
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Leaf wetness, water and equipment
Leaf-wetness sensors can identify prolonged wet conditions associated with disease risk, but they do not diagnose disease. Interpret them alongside crop, temperature, humidity, airflow and disease-management knowledge. The repository’s Decentlab DL-LWS entry describes leaf-wetness monitoring applications that include greenhouse and soil-less growing.
Rank #3
- SE01-LB LoRaWAN Soil Moisture & EC Sensor
- The Dragino SE01-LB is a LoRaWAN Soil Moisture & EC Sensor for IoT of Agriculture
- It is designed to measure the soil moisture of saline-alkali soil and loamy soil
- The soil sensor uses the FDR method to calculate soil moisture with the soil temperature and conductivity compensation
- Sensors, Smart Agriculture
Useful system-health measurements include tank level, water flow, pump run state, valve state, fan or heater status, vent position, leak detection, electrical-panel temperature and backup-power status. These can reveal equipment problems before environmental readings show plant stress.
Select reporting intervals and alerts
Set reporting frequency according to how quickly a condition can become harmful and how quickly an operator needs to respond. The intervals below are illustrative engineering starting points, not agronomic requirements or guaranteed LoRaWAN settings.
| Measurement | Illustrative starting interval | Purpose |
|---|---|---|
| Air temperature and humidity | 1–5 minutes | Identify relatively rapid climate changes. |
| Soil or substrate moisture | 5–30 minutes | Support irrigation decisions without excessive traffic. |
| CO₂ during enrichment | 1–5 minutes | Observe enrichment, depletion and ventilation effects. |
| Light or PAR | 1–5 minutes or event-based aggregation | Track intensity and calculate daily exposure. |
| Tank level | 5–30 minutes, plus threshold event | Identify supply issues. |
| Equipment state | On change plus periodic heartbeat | Detect failures and stale reports. |
| Battery voltage | Hourly or daily | Identify maintenance needs. |
The workable interval depends on the regional radio parameters, payload size, number of devices, gateway capacity, battery budget and local radio rules. A 15-minute reporting interval should not be described as real-time control. State the sampling interval and expected alert delay wherever response speed matters.
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Combine scheduled telemetry with threshold events and a periodic heartbeat. Configure alerts for out-of-range readings, low battery, missing reports, gateway offline status and implausible values. Use a delay window and separate return-to-normal threshold (hysteresis) to reduce repeated alerts as a measurement fluctuates around a limit.
Plan zones and place sensors carefully
Map crop areas, irrigation zones, shade and light patterns, heating and ventilation equipment, doors, vents, tanks, pump rooms and potential gateway locations. Split the greenhouse into monitoring zones where environmental conditions or irrigation behavior differ materially; one central sensor can miss local hot, cold, dry or humid pockets.
- Air sensors: Position near crop-canopy height with airflow around the sensing element, away from direct sun, spray, heaters, cooling pads and fan discharge.
- Root-zone probes: Place at the effective root depth in representative beds or containers, using the same substrate as the crop. Choose a meaningful offset from irrigation emitters.
- CO₂ sensors: Locate where readings represent the crop zone, not a gas outlet or strong air jet.
- Light sensors: Mount level and unobstructed at the crop-relevant measurement plane; consider hanging baskets, structural members and supplemental lighting.
- Gateway: Place it above major obstructions where practical, with an appropriate antenna and reliable backhaul. Keep it out of a metal cabinet unless the antenna is properly externalized.
Condensation, chemical exposure, irrigation splash and poor airflow can cause drift or false readings. Check that the enclosure and probes—not just the sensor body—are suitable for the actual environment. A greenhouse installation should be commissioned at the final mounting locations, not judged by a radio test at the entrance.
Rank #4
- PRECISE ACCURACY MEASUREMENT. - Soil Moisture Sensor provides an external probe for receiving accurate and instantaneous information on soil moisture content, temperature, and electrical conductivity, offering Research-grade accuracy in multiple soil media.
- DASHBOARD. - Cloud dashboard will presents important graphics of data collected from Soil Moisture sensors and help users to make relevant decisions in advance. You can drag and drop any graphs onto your dashboard and read data in a visualized manner.
- EASY INSTALLATION AND CONFIGURATION. - The IoT-S500TH features NFC configuring to provide better operational efficiency. With the installation of Toolbox APP / Toolbox PC, users can easily monitoring and configuring of LoRaWAN sensors both on mobile devices and PC.
- LoRaWAN NETWORK COMPATIBILITY. - LINOVISION LoRaWAN sensors are compatible with industry standard LoRaWAN Gateways.
- REMOTE MONITORING 7*24. - By using Cloud Web and mobile App, users can remotely monitor the growing environment anywhere and anytime.
Choose devices, gateway and network service
A complete deployment includes sensor nodes, a gateway, a LoRaWAN network server and an application. Depending on the system, control hardware is a separate layer. AWS IoT Core for LoRaWAN is one managed option; its documentation describes gateway management, device onboarding and routing into AWS services. It supports LoRaWAN 1.0.x and 1.1 devices, and its qualified gateway model uses LoRa Basics Station-compatible gateways. See the AWS IoT Core for LoRaWAN documentation and device onboarding guidance.
The Things Network device repository lists greenhouse-relevant devices. Its Decentlab DL-GMM entry describes a greenhouse multi-monitor for PAR, temperature, humidity, barometric pressure and CO₂. Treat repository listings as a way to identify devices, not a substitute for checking the exact model, regional variant and current vendor specifications.
Before purchasing, verify the following for each device and gateway:
- Country-specific frequency band and matching regional version.
- LoRaWAN version, certification status and network-server compatibility.
- Measurement range, accuracy, calibration method and expected maintenance.
- Enclosure suitability, including probes, connectors and battery access.
- Payload decoder availability, support and ability to retain raw payloads.
- Battery type, replacement process, external-probe options and configuration support.
- Data export, API access and ability to change network or application platforms.
- Warranty, local support, replacement availability and total operating cost.
Radio rules and frequency plans differ by region; do not assume a product configured for one market is legal or compatible in another. A public or community network may also have coverage or service terms unsuitable for production use. Confirm those conditions at the site before relying on it.
Deploy and commission in a controlled sequence
- Define decisions: For each measurement, record what action it supports, the required accuracy, alert threshold, response time and consequence of a missing reading.
- Map zones: Mark crop, irrigation, lighting and climate-control zones, plus gateway and backhaul locations.
- Select the architecture: Choose private, managed or community LoRaWAN, or a hybrid arrangement with wired controls. For a small site, a private gateway and local application may reduce cloud dependency; distributed operations may favor a managed service.
- Confirm regional compatibility: Match node and gateway frequency plan, then check local transmit-power, duty-cycle and spectrum rules.
- Install the gateway: Configure its frequency plan, antenna, backhaul and network-server connection. Provide stable power and a restart or backup strategy. AWS’s getting-started guide describes connecting gateways and devices to its service.
- Onboard each device: Record its DevEUI, JoinEUI or AppEUI as applicable, OTAA AppKey where used, model, firmware, frequency plan, location, payload format, serial number and calibration date. Prefer OTAA provisioning for ordinary deployments unless device or operational requirements call for another method. Keep credentials out of public documents and shared source repositories.
- Decode and normalize data: Convert payloads to consistent fields such as zone, device, timestamp, temperature, humidity, CO₂, moisture, EC, PAR, battery voltage, RSSI and SNR. Retain the raw payload, frame counter, gateway identifier, decoder version and data-quality flags for troubleshooting.
- Validate measurements: Compare temperature and humidity with a calibrated reference, test moisture readings in the installed substrate, verify CO₂ against a trusted instrument and check light readings under representative conditions. Record offsets and calibration dates.
- Test alerts and missing-data behavior: Trigger expected thresholds, interrupt a device or backhaul deliberately where safe, and confirm the dashboard identifies stale values and recovery.
- Add automation only after validation: Test local interlocks, manual overrides, fail-safe states and loss-of-communications behavior before allowing actuators to respond automatically.
Build a dashboard that exposes data quality
A useful dashboard should show current readings by greenhouse and zone, trends, alert status, device battery, last-seen time, RSSI and SNR, gateway status, equipment events and data gaps. Make the age of each reading obvious: a last-known value without a timestamp can look current after a device has stopped reporting.
Derived measures can include VPD, dew point, daily light integral, irrigation duration, temperature-hours outside limits, humidity-duration events and battery-consumption trends. Keep source measurements and the assumptions behind each calculation so later users can interpret or recalculate them. Retain enough history to compare day and night, irrigation cycles, crop stages, seasonal changes, maintenance and control adjustments. Data export or an API reduces the risk of being locked into a dashboard.
Best Value
- LDS02 - LoRaWAN Door Sensor
- The Dragino LDS02 is a LoRaWAN Door Sensor
- It detects door open/close status and uplinks to IoT server via LoRaWAN network
- user can see the door status, open time, open counts in the IoT Server
- Door & Window, Sensors
Keep monitoring separate from safety-critical control
Monitoring detects conditions; automation chooses an action; actuators carry it out. Put time-critical and safety-relevant logic in a local PLC, greenhouse controller, industrial computer or suitable local controller so basic operation does not depend solely on a gateway, network server, cloud service or Internet link.
Use local schedules, watchdogs, manual overrides, interlocks and defined fail-safe states. A cloud rule should not be the only protection against an overheating heater, dry-running pump, stuck valve, storm-exposed vent or CO₂ enrichment running while vents are open. Cloud alerts also do not replace local audible or visual alarms for critical hazards.
LoRaWAN relay nodes are not automatically industrial motor controllers. Pumps, heaters, fans and mains-powered equipment may need contactors, overload protection, fusing, grounding, isolation and qualified electrical installation.
Compare LoRaWAN with alternatives
| Technology | Strengths | Trade-offs | Often suits |
|---|---|---|---|
| LoRaWAN | Low-power periodic telemetry, long-range potential and many nodes per gateway. | Low data rate, site-dependent radio performance and limited downlink capacity. | Distributed battery sensors and detached greenhouse or irrigation zones. |
| Wi-Fi | High bandwidth and common local integration. | Coverage may be weak across structures; battery-operated devices need careful power planning. | Mains-powered controllers, cameras and sites with reliable access-point coverage. |
| Cellular IoT | Can avoid a local gateway where carrier coverage is available. | Carrier dependency, potential recurring service costs and device power considerations. | Remote or distributed locations where gateway installation is impractical. |
| Zigbee or Thread | Mesh networking and local smart-building integration. | Performance depends on topology and powered routing nodes; greenhouse range needs testing. | Compact installations with a suitable local mesh infrastructure. |
| Wired RS-485 or industrial fieldbus | Predictable communication and strong fit for fixed control equipment. | Cabling, installation labor, grounding and lightning protection require planning. | Fixed equipment and control functions where radio uncertainty is undesirable. |
| Point-to-point LoRa | Can provide a simple custom radio link. | Builder must handle addressing, security, acknowledgements, retries and scaling. | Small projects with a developer able to maintain both endpoints. |
Estimate the full cost of ownership
There is no reliable universal per-greenhouse price: hardware counts, sensor grade, installation, network service and maintenance vary widely. Compare systems using the full lifecycle rather than sensor purchase price alone:
Total cost = sensor nodes + gateway + antennas and enclosures + installation + network-server fees + dashboard/cloud fees + cellular backhaul, if used + batteries and replacements + calibration + maintenance + actuator and electrical-control hardware.
A small greenhouse may need only a few certified temperature/humidity and moisture nodes, a regional gateway and a simple dashboard, with separate local control hardware. A commercial multi-bay operation may justify zone-based sensing, commercial probes, CO₂ or PAR where agronomically useful, and documented calibration and replacement support. AWS describes its LoRaWAN service as pay-for-use and notes a Free Tier for new customers, but charges depend on usage, region and related AWS services; consult its official pricing page for current terms rather than treating any single figure as a greenhouse quote.
Quick Recap
Troubleshoot common failures
- Device does not join: Check regional frequency plan, identifiers and credentials, gateway connectivity and network-server configuration.
- Device joins but values are missing or wrong: Confirm the payload decoder, decoder version and field mapping; compare decoded output with a known raw packet.
- Uplinks are intermittent: Check antenna placement, gateway visibility, obstructions and actual signal indicators at the sensor location.
- Battery drains quickly: Review reporting frequency, payload size, radio conditions, temperature and downlink activity against the battery budget.
- Readings drift or spike: Inspect for condensation, splash, poor airflow, damaged probes and placement bias; compare with a reference and recalibrate or replace as needed.
- Dashboard shows stale values: Display last-seen time and alert on missed heartbeats; check the node, gateway and backhaul rather than assuming the displayed value is current.
- False or repeated alerts: Review placement, data quality, thresholds, delay windows and hysteresis.
- Cloud or Internet service is unavailable: Confirm that local control and alarms continue safely, and consider local buffering or cellular backhaul failover where remote visibility is critical.
- Pump or valve does not respond: Check the local controller, interlocks, actuator power and electrical protection. Do not assume a valid sensor reading proves an actuator operated.
Buyer checklist
- Does each proposed measurement support a specific crop or operational decision?
- Are accuracy, calibration and maintenance appropriate to the variable and environment?
- Does the exact regional device variant work with the chosen gateway and network server?
- Has coverage been checked at final mounting locations?
- Can the system alert on missing data, low battery and gateway failure as well as threshold breaches?
- Can operators access raw data, export history and change platforms if needed?
- Are local fallback controls, interlocks and qualified electrical installation included?
- Does the total cost include installation, service, calibration, replacement and support?
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
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