Invernadero inteligente y agricultura 4.0

In Colombia, agricultural exports have become notoriously prevalent in recent years, causing the creation of new methods capable of increasing production in order to meet the global demands. A very efficient option is the use of greenhouses, given their low building cost, ease of construction, ability to protect crops from natural phenomena and plagues, and the possibility to keep the internal temperature steady during day and night, thus allowing crops to grow fast and healthy. Nowadays, advancements in electronics have allowed boosting the positive effects of these environments, which is why this document introduces a procedure for the implementation of an automated pyramid-type greenhouse, utilizing techniques related to Precision Agriculture (PA) and based on concepts related to the Internet of Things (IoT) for remote monitoring through emerging communication technologies such as the NFRL2401 cards and the Arduino Nano and Mega boards. Inside the greenhouse, variables such as temperature and ambient humidity are measured and controlled via the PCE-P30U Universal Input Signal Converter Data Logger, while ground humidity is monitored by ZD510 capacitive sensors. Outside, variables such as temperature, ambient humidity, negative and positive pressure, and wind speed are measured. Data obtained is taken wirelessly to the server using Windows Server 2019 Datacenter, with Broker MQTT EMQ-X services and MYSQL databases, providing a suitable and efficient environment for agricultural research processes. With the procedure developed in this document, a baseline is proposed for the implementation of a smart greenhouse that can be replicated and used as a test system for smart sowing processes, adapting to the different climate and production conditions of the country.En Colombia, la exportación agrícola ha crecido en los últimos años, motivando la creación de nuevos métodos que incrementen la producción para satisfacer la demanda mundial. El uso de invernaderos es una opción bastante eficiente, dados sus bajos costos de construcción, su habilidad para proteger cultivos de fenómenos naturales y plagas, y la posibilidad de mantener la temperatura interna estable durante el día y la noche, lo cual hace que el fruto crezca rápido y saludable. En la actualidad, los avances en electrónica han permitido potencializar los efectos positivos de estos espacios, por lo cual en este texto se presenta un procedimiento para la implementación de un invernadero automatizado de tipo piramidal, utilizando técnicas relacionadas con la Agricultura de Precisión (AP) y partiendo de conceptos relacionados con el internet de las cosas (IoT) para el monitoreo remoto a través de tecnologías emergentes de comunicación como las tarjetas NFRL2401 y placas Arduino Nano y Mega. Al interior del invernadero se miden y controlan variables como la temperatura y humedad del ambiente por medio de la PCE-P30U Universal Input Signal Converter Data Logger, mientras que la humedad del suelo es monitoreada por medio de sensores capacitivos ZD510. En el exterior, se miden variables como la temperatura, la humedad del ambiente, presión positiva y negativa y la velocidad del viento. Los datos obtenidos son llevados inalámbricamente a un servidor que utiliza el Windows Server 2019 Datacenter, con servicios Broker MQTT EMQ-X y bases de datos MYSQL, propiciando un ambiente apto y eficiente para la realización de procesos en investigación agrícola. Con el procedimiento desarrollado en este documento, se propone una línea de base para la implementación de un invernadero inteligente que pueda ser replicado y sirva como sistema de prueba en procesos inteligentes de siembra, adaptándose a la diferentes condiciones climáticas y productivas del país

Proposal of architecture for IoT solution for monitoring and management of plantations

The world population growth is increasing the demand for food production. Furthermore, the reduction of the workforce in rural areas and the increase in production costs are challenges for food production nowadays. Smart farming is a farm management concept that may use Internet of Things (IoT) to overcome the current challenges of food production This work presents a systematic review of the existing literature on smart farming with IoT. The systematic review reveals an evolution in the way data are processed by IoT solutions in recent years. Traditional approaches mostly used data in a reactive manner. In contrast, recent approaches allowed the use of data to prevent crop problems and to improve the accuracy of crop diagnosis. Based on the finds of the systematic review, this work proposes an architecture of an IoT solution that enables monitoring and management of crops in real time. The proposed architecture allows the usage of big data and machine learning to process the collected data. A prototype is implemented to validate the operation of the proposed architecture and a security risk assessment of the implemented prototype is carried out. The implemented prototype successfully validates the proposed architecture. The architecture presented in this work allows the implementation of IoT solutions in different scenarios of farming, such as indoor and outdoor

Towards rapid modeling and prototyping of indoor and outdoor monitoring applications

Nowadays, the capability to remotely monitor indoor and outdoor environments would allow to reduce energy consumption and improve the overall management and users’ experience of network application systems. The most known solutions adopting remote control are related to domotics (e.g., smart homes and industry 4.0 applications). An important stimulus for the development of such smart approaches is the growth of the Internet of Things (IoT) technologies and the increasing investment in the development of green houses, buildings, and, in general, heterogeneous environments. While the benefits for the humans and the environment are evident, a pervasive adoption and distribution of remote monitoring solutions are hindered by the following issue: modeling, designing, prototyping, and further developing the remote applications and underlying architecture require a certain amount of time. Moreover, such systems must be often customized on the basis of the need of the specific domain and involved entities. For such reasons, in this paper, we provide the experience made in addressing some relevant indoor and outdoor case studies through IoT-targeted tools, technologies and protocols, highlighting the advantages and disadvantages of the considered solutions as well as insights that can be useful for future practitioners

IoT-Based Sensor Data Fusion for Determining Optimality Degrees of Microclimate Parameters in Commercial Greenhouse Production of Tomato

Optimum microclimate parameters, including air temperature (T), relative humidity (RH) and vapor pressure deficit (VPD) that are uniformly distributed inside greenhouse crop production systems are essential to prevent yield loss and fruit quality. The objective of this research was to determine the spatial and temporal variations in the microclimate data of a commercial greenhouse with tomato plants located in the mid-west of Iran. For this purpose, wireless sensor data fusion was incorporated with a membership function model called Optimality Degree (OptDeg) for real-time monitoring and dynamic assessment of T, RH and VPD in different light conditions and growth stages of tomato. This approach allows growers to have a simultaneous projection of raw data into a normalized index between 0 and 1. Custom-built hardware and software based on the concept of the Internet-of-Things, including Low-Power Wide-Area Network (LoRaWAN) transmitter nodes, a multi-channel LoRaWAN gateway and a web-based data monitoring dashboard were used for data collection, data processing and monitoring. The experimental approach consisted of the collection of meteorological data from the external environment by means of a weather station and via a grid of 20 wireless sensor nodes distributed in two horizontal planes at two different heights inside the greenhouse. Offline data processing for sensors calibration and model validation was carried in multiple MATLAB Simulink blocks. Preliminary results revealed a significant deviation of the microclimate parameters from optimal growth conditions for tomato cultivation due to the inaccurate timer-based heating and cooling control systems used in the greenhouse. The mean OptDeg of T, RH and VPD were 0.67, 0.94, 0.94 in January, 0.45, 0.36, 0.42 in June and 0.44, 0.0, 0.12 in July, respectively. An in-depth analysis of data revealed that averaged OptDeg values, as well as their spatial variations in the horizontal profile were closer to the plants’ comfort zone in the cold season as compared with those in the warm season. This was attributed to the use of heating systems in the cold season and the lack of automated cooling devices in the warm season. This study confirmed the applicability of using IoT sensors for real-time model-based assessment of greenhouse microclimate on a commercial scale. The presented IoT sensor node and the Simulink model provide growers with a better insight into interpreting crop growth environment. The outcome of this research contributes to the improvement of closed-field cultivation of tomato by providing an integrated decision-making framework that explores microclimate variation at different growth stages in the production season

Smart Greenhouse and Agriculture 4.0

In Colombia, agricultural exports have become notoriously prevalent in recent years, causing the creation of new methods capable of increasing production in order to meet the global demands. A very efficient option is the use of greenhouses, given their low building cost, ease of construction, ability to protect crops from natural phenomena and plagues, and the possibility to keep the internal temperature steady during day and night, thus allowing crops to grow fast and healthy. Nowadays, advancements in electronics have allowed boosting the positive effects of these environments, which is why this document introduces a procedure for the implementation of an automated pyramid-type greenhouse, utilizing techniques related to Precision Agriculture (PA) and based on concepts related to the Internet of Things (IoT) for remote monitoring through emerging communication technologies such as the NFRL2401 cards and the Arduino Nano and Mega boards. Inside the greenhouse, variables such as temperature and ambient humidity are measured and controlled via the PCE-P30U Universal Input Signal Converter Data Logger, while ground humidity is monitored by ZD510 capacitive sensors. Outside, variables such as temperature, ambient humidity, negative and positive pressure, and wind speed are measured. Data obtained is taken wirelessly to the server using Windows Server 2019 Datacenter, with Broker MQTT EMQ-X services and MYSQL databases, providing a suitable and efficient environment for agricultural research processes. With the procedure developed in this document, a baseline is proposed for the implementation of a smart greenhouse that can be replicated and used as a test system for smart sowing processes, adapting to the different climate and production conditions of the country

Smart Greenhouse and Agriculture 4.0

In Colombia, agricultural exports have become notoriously prevalent in recent years, causing the creation of new methods capable of increasing production in order to meet the global demands. A very efficient option is the use of greenhouses, given their low building cost, ease of construction, ability to protect crops from natural phenomena and plagues, and the possibility to keep the internal temperature steady during day and night, thus allowing crops to grow fast and healthy. Nowadays, advancements in electronics have allowed boosting the positive effects of these environments, which is why this document introduces a procedure for the implementation of an automated pyramid-type greenhouse, utilizing techniques related to Precision Agriculture (PA) and based on concepts related to the Internet of Things (IoT) for remote monitoring through emerging communication technologies such as the NFRL2401 cards and the Arduino Nano and Mega boards. Inside the greenhouse, variables such as temperature and ambient humidity are measured and controlled via the PCE-P30U Universal Input Signal Converter Data Logger, while ground humidity is monitored by ZD510 capacitive sensors. Outside, variables such as temperature, ambient humidity, negative and positive pressure, and wind speed are measured. Data obtained is taken wirelessly to the server using Windows Server 2019 Datacenter, with Broker MQTT EMQ-X services and MYSQL databases, providing a suitable and efficient environment for agricultural research processes. With the procedure developed in this document, a baseline is proposed for the implementation of a smart greenhouse that can be replicated and used as a test system for smart sowing processes, adapting to the different climate and production conditions of the country

Smart Greenhouse and Agriculture 4.0

In Colombia, agricultural exports have become notoriously prevalent in recent years, causing the creation of new methods capable of increasing production in order to meet the global demands. A very efficient option is the use of greenhouses, given their low building cost, ease of construction, ability to protect crops from natural phenomena and plagues, and the possibility to keep the internal temperature steady during day and night, thus allowing crops to grow fast and healthy. Nowadays, advancements in electronics have allowed boosting the positive effects of these environments, which is why this document introduces a procedure for the implementation of an automated pyramid-type greenhouse, utilizing techniques related to Precision Agriculture (PA) and based on concepts related to the Internet of Things (IoT) for remote monitoring through emerging communication technologies such as the NFRL2401 cards and the Arduino Nano and Mega boards. Inside the greenhouse, variables such as temperature and ambient humidity are measured and controlled via the PCE-P30U Universal Input Signal Converter Data Logger, while ground humidity is monitored by ZD510 capacitive sensors. Outside, variables such as temperature, ambient humidity, negative and positive pressure, and wind speed are measured. Data obtained is taken wirelessly to the server using Windows Server 2019 Datacenter, with Broker MQTT EMQ-X services and MYSQL databases, providing a suitable and efficient environment for agricultural research processes. With the procedure developed in this document, a baseline is proposed for the implementation of a smart greenhouse that can be replicated and used as a test system for smart sowing processes, adapting to the different climate and production conditions of the country

Internet of Things Applications in Precision Agriculture: A Review

The goal of this paper is to review the implementation of an Internet of Things (IoT)-based system in the precision agriculture sector. Each year, farmers suffer enormous losses as a result of insect infestations and a lack of equipment to manage the farm effectively. The selected article summarises the recommended systematic equipment and approach for implementing an IoT in smart farming. This review's purpose is to identify and discuss the significant devices, cloud platforms, communication protocols, and data processing methodologies. This review highlights an updated technology for agricultural smart management by revising every area, such as crop field data and application utilization. By customizing their technology spending decisions, agriculture stakeholders can better protect the environment and increase food production in a way that meets future global demand. Last but not least, the contribution of this research is that the use of IoT in the agricultural sector helps to improve sensing and monitoring of production, including farm resource usage, animal behavior, crop growth, and food processing. Also, it provides a better understanding of the individual agricultural circumstances, such as environmental and weather conditions, the growth of weeds, pests, and diseases

Research Trends on Greenhouse Engineering Using a Science Mapping Approach

Horticultural protected cultivation has spread throughout the world as it has proven to be extremely effective. In recent years, the greenhouse engineering research field has become one of the main research topics within greenhouse farming. The main objectives of the current study were to identify the major research topics and their trends during the last four decades by analyzing the co-occurrence network of keywords associated with greenhouse engineering publications. A total of 3804 pertinent documents published, in 1981-2021, were analyzed and discussed. China, the United States, Spain, Italy and the Netherlands have been the most active countries with more than 36% of the relevant literature. The keyword cluster analysis suggested the presence of five principal research topics: energy management and storage; monitoring and control of greenhouse climate parameters; automation of greenhouse operations through the internet of things (IoT) and wireless sensor network (WSN) applications; greenhouse covering materials and microclimate optimization in relation to plant growth; structural and functional design for improving greenhouse stability, ventilation and microclimate. Recent research trends are focused on real-time monitoring and automatic control systems based on the IoT and WSN technologies, multi-objective optimization approaches for greenhouse climate control, efficient artificial lighting and sustainable greenhouse crop cultivation using renewable energy