Design and Development of Smart Agricultural Greenhouse

Abstract

Food insecurity across the globe has necessitated the need to optimize crops productivity through automation and Internet of Things (IoT). This research was carried out to develop a smart greenhouse system where the soil nutrient level, air temperature and soil moisture content can be closely monitored through sensors and the Internet. The sensors – major input components of the structure – sent information to a NodeMCU ESP8266 microcontroller for interpretation, configuration and necessary actions by the output components of the smart structure. The output components of the smart structure are the liquid-crystal display (LCD), water pump, fan, heater and relay modules, while the C++ programming language was used. Remarkably, the intelligence aspect of the smart greenhouse is built on the smart algorithm. Based on the performance evaluation of the various system units, the irrigation, cooling, heating and fertilization units have an accuracy of 85%, 90%, 90% and 85% respectively. Interestingly, the performance rating of the prototype was very encouraging, which makes this smart system a reliable material to combat global food insecurity.

Keywords

• Algorithm
• Food security
• Programming language
• Sensors
• Smart greenhouse

References

1. Awad NA, Mohamed E, Emad HE, Ahmed SMI, Yasser SGA, Mohamed SG, Reda MYZ, Rokayya S, Ebtihal K, Uguru H and Khaled S (2022). Evaluation of the effect of elite jojoba strains on the chemical properties of its seed oil. Molecules, 27: 3904-3913.
2. Ballard R (1996). Methods of inventory monitoring and measurement. Logistics Information Management, 9(3): 11-18.
3. Ben Ayed R and Hanana M (2021). Artificial intelligence to improve the food and agriculture sector. Journal of Food Quality, 2021: 1-7.
4. Cao J (2022). Coordinated development mechanism and path of agricultural logistics ecosystem based on big data analysis and IoT assistance. Acta Agriculturae Scandinavica Section B Soil and Plant Science, 72(1): 214-224.
5. Ekruyota OG and Uguru, H (2021). Characterizing the mechanical properties of eggplant (Melina F1) fruits, for the design and production of agricultural robots. Direct Research Journal of Engineering and Information Technology. 8:21-29.
6. Goap A, Sharma D, Shukla A K and Rama Krishna C (2018). An IoT based smart irrigation management system using Machine learning and open source technologies. Computers and Electronics in Agriculture, 155: 41-49.
7. Idama and Ekruyota OG (2023). Design and development of a model smart stoarage system. Turkish Journal of Agricultural Engineering Research, 4(1): 125-132.
8. Ma Y, Qu L, Wang W, Yang X and Lei T (2016). Measuring soil water content through volume/mass replacement using a constant volume container. Geoderma, 271: 42-49.

9. Nurhasanah R, Savina L, Nata ZM and Zulkhair I (2021). Design and implementation of IoT based automated tomato watering system Using ESP8266. Journal of Physics: Conference Series. 1898: 1-8.
10. Ogidan OK, Onile AE and Adegboro OG (2019). Smart irrigation system: a water management procedure. Agricultural Sciences, 10: 25-31.
11. O’Reilly (2021). Introducing C# and the NET Framework. Available online at: https://www.oreilly.com/library/view/c-40-in/9781449379629/ch01.html. Retrieved on May, 2023.
12. Ramirez-Asis E, Bhanot A, Jagota V, Chandra B, Hossain S, Pant K and Almashaqbeh HA (2022). Smart logistic system for enhancing the farmer-customer corridor in smart agriculture sector using artificial intelligence. Journal of Food Quality, 22; 7486974-7486982.
13. Sahni V, Srivastava S and Khan R (2021). Modelling techniques to improve the quality of food using artificial intelligence. Journal of Food Quality, 2021, 1-10.
14. Sensor (2023). Sensors. Available online at: https://how2electronics.com/measure-soil-nutrient-using-arduino-soil-npk-sensor/ Retrieved on May, 2023.
15. Srivastava P, Bajaj M and Rana AS (2018). Overview of ESP8266 Wi-Fi module based smart irrigation system using IOT. Fourth International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB): 1-5.
16. Statista (2022). Crop production. Available online at: https://www.statista.com/statistics/1265139/agriculture-as-a-share-of-gdp-in-africa-by-country/ Retrieved on May, 2023.
17. Uguru H, Akpokodje OI, Rokayya S, Amani HA, Almasoudi A and Abeer G A (2022). Comprehensive assessment of the effect of various anthropogenic activities on the groundwater quality. Science of Advanced Materials, 14: 462-474.
18. Xue R, Shen Y and Marschner P (2017). Soil water content during and after plant growth influence nutrient availability and microbial biomass. Journal of Soil Science and Plant Nutrition, 17(3): 702-715.