Real-time monitoring & control of greenhouse conditions parameters with Lora WAN, cloud computing, Io T , and solar energy integration.

Tomatoes grown in one of DeKUT greenhouses.

A greenhouse is a structure built with walls and roof made mainly of transparent material, such as glass, polythene cover, mesh or net , which plants requiring regulated climatic conditions are grown.Optimum conditions have to be provided. These structures range in size from small sizes to industrial-sized buildings. They can be established anywhere especially conventional type. However, the integrated rooftop greenhouses (IRTGs) are versatile in urban centers and cities where land use is limited. The puzzle remains that how can optimum conditions be achieved in greenhouses?

This is a short master masterpiece that focuses on latest trends in technology yet showing their integration in agriculture related fields.The aim of this integration is to increase crop yields, cut down on cost of production, conserve energy and other limited resources in farms. The base line being using this technologies to achieve artificial intelligence in greenhouse operation and crop production.

Deployed and raise gateway on top of a building for easy radio mapping and achieving line of sight.

Assembled greenhouse monitoring and control Io T rugged device powered by solar assembled on bench.

With the world evolving into futurism sophisticated entities, cloud computing, Io T, machine learning, data science, green energy and Lora WAN technologies are gaining fast access and preference into the field of agriculture.Yet other more pieces to come.This technologies are used to solve agriculture related problems such as erosion, crop pests and diseases control, water & energy conservation and monitoring and control of greenhouse parameters.

Real-time greenhouse conditions monitoring and control is important since crops require optimum conditions for growth. Immediate conditions capable of affecting crops in the greenhouse directly if not controlled are ; Temperature, humidity and soil moisture. Moreover, light intensity and air quality conditions are significant too. light intensity is monitored for the purpose of crops leaves development and air quality for the sake of personnel working in the structures.Farmers face the problems of temperature fluctuations in greenhouses that cause high rates of transpiration, withering, preference of crop pests and diseases such as blight.Also fluctuations of humidity levels cause problems to crops with fungi spread in high humidity.Low or high soil moisture content may cause crops to wither or root rot respectively among many problems related to greenhouse conditions. Greenhouses use chemicals and if air quality is not monitored can cause respiratory complications to personnel working in these structures.This remains a big problem since there are no special tools to monitor this conditions.Can you use thermometer? Go into the greenhouse to feel the condition basing on your comfort? Dip finger to the soil to measure level of moisture?

Block diagram showing the process of real-time monitoring and control of greenhouse conditions.

In real-time monitoring and control of greenhouses, the temperature, relative humidity, soil moisture, light intensity and air quality sensors are connected to programmed nucleo micro controller that is the best board known for its low power consumption.Greenhouse environment condition data collected from the greenhouse is sent wireless and remote to the cloud server like the things network(TTN) via a Long range wide area network (Lora WAN) gateway.This gateway can operate 2–4 km diameter in obstacle dominated areas and 50- 70 km in line of sight.The shields on the micro controllers operate at radio frequencies with gateway to enhance multi channel communication with low power consumption both up link and down link .The gateway does general edge analytics and sends the most consistent data to the cloud server.From TTN, real-time - seamless data is channeled through a data pipeline such as node-red using APIs to database.One can opt to use any time series, nosql database such as elastic-search or influx db. At the same time visualized in real-time on high end open source visualization tool such as grafana or kibana is done. From the visualization UIs queries and searches can be done on indexes to show trends and real time streams and the nature of the data.Using APIs this data is sent to analytic tools such as Jupiter notebook, google colab.research for analysis. With time and with accumulation of enough data ,machine learning can be done on this data using 5 parameters or variables.Model trained on this data will provide predictions and inference. Feedback is sent back to mobile phones in SMS, tweet or email notification alert.The feedback is sent to the greenhouse via down link to control the peripheral devices with respect to the prediction on a certain parameter,such as pumps and solenoid valves for irrigation, fans and side nets for temperature control and motors among many appliances that can be controlled.

Above shows water tank between two greenhouses that supplies water for irrigation to greenhouses.

The aspect of green energy is employed here to power the boards since they consume low energy and solar energy can he harnessed anywhere.The future of energy is renewable energy,Therefore, small solar panels can power up to 10 of these Io T devices and run smoothly.This system is highly scalable to meet the demands of an expanding greenhouse farm with the gateway capable of connecting many devices to cloud servers.

Relevant open source tools to use are ;the things speak, the things network, node-red, elastic search, kibana, influx db, Cassandra, mongodb, grafana, chronograph, Kafka, twillio, ARM Mbed compilers and connectors and any other tools you might find amusing and fun to work with.

Clap once, twice, three times and share. To conserve water, energy,provide optimum conditions and cut down cost of operation in our farms.