User:Rshon Shaked/sandbox

1        Introduction and Problem Definition

The worldwide farming sector has been put under great strain as a result of climate change, decreasing resources, and increasing populations. As unpredictability rises, growers are increasingly using cutting-edge technologies to improve production efficiency and crop resilience. In agriculture, the Internet of Things (IoT) is more prevalent than ever before, and smart greenhouses are a great example.

The Internet of Things (IoT) includes using sensors to provide information on your device, instead of manually carrying out the job. To manage this extensive data and analyze it accurately, an internet connection is needed. With the help of IoT, you receive alerts regarding fertilization and irrigation.

Greenhouses are controlled environments used for cultivating plants, providing shelter from external weather while allowing for tailored conditions. However, traditional greenhouse management relies heavily on manual intervention for tasks like temperature, irrigation, and ventilation, which can be time-consuming and error prone. Designing an automatic system for greenhouses would enhance efficiency by precisely regulating factors like temperature, humidity, and soil moisture, leading to optimized plant growth, resource conservation, reduced labor demands, and improved crop yields.

Smart greenhouse tech offers an efficient, green way to farm, especially in resource-poor, harsh climates like the Middle East and Africa. Here, smart greenhouses beat natural limits and harsh weather, giving crops an ideal place to grow. This means they can ensure stable crops even in dry or hot conditions, reducing reliance on traditional farming.

Smart greenhouses don’t just raise efficiency and quality; they also use water and energy better and cut labor costs. This is big for food security and sustainable farming, especially in areas with tough climates. As tech improves and costs drop, smart greenhouses will play a bigger role in global farming, especially in helping areas with few resources and tough climates.

Traditional greenhouse management relies heavily on manual intervention for controls like temperature, irrigation, and ventilation, which leads to inefficiencies and room for human errors. This project addresses such limitations by leveraging IoT technology to optimize and automate greenhouse management. Through the use of sensors, actuators, and cloud-based services, the system is envisioned to regulate environmental parameters with precision, conserve resources, and improve crop production. The three-tier structure - perception (sensors & actuators), network (data transfer), and application (cloud & user interface) - facilitates real-time data gathering, automatic responses, and remote monitoring.

The motivation behind this project arises from the necessity to overcome the drawbacks presented by conventional greenhouse cultivation, i.e., suboptimal exploitation of resources, manually intensive operations, and uncertainty of growth conditions.

Through the meticulous regulation of irrigation, lighting, and ventilation according to real-time data from sensors, this project achieves optimum utilization of resources with minimum wastage generation. Automation hinges on less human intervention, thereby conserving time and resources for greenhouse managers. Further, by ensuring stable and ideal environmental conditions, the system optimizes plant growth and enhances crop production yields. The target audience consists of greenhouse owners, agricultural producers, commercial farm enterprises, horticulturists, and research institutions looking to optimize operational efficiency, minimize costs, and encourage sustainable agriculture. This project offers an economically viable and adaptable solution that tackles some of the primary challenges of operating greenhouses.

This project is novel in the utilization of open-source platforms, such as ThingSpeak, that provide data storage and analysis capabilities, the application of sophisticated algorithms to enable automated control, and a modular design for simple expansion and customization. This project, Smart Greenhouse, has great potential to transform greenhouse farming with the use of IoT technology. The novelty in this project lies in the usage of open-source platforms, auto-control logic, scalability, and decision-making through data. With the improvement of yields, reduction in the utilization of resources, and reduction of expenses, this project promotes sustainable agriculture and helps in an effective and efficient food system.

2        Motivation & Objectives

2.2      Aim

The primary aim of an innovative greenhouse is to optimize plant growth and resource utilization through automated monitoring and control.

2.3      Objective

1.     Automated Monitoring: Continuously track temperature, humidity, soil moisture, and light intensity.

2.     The temperature sensor monitors the internal climate of the greenhouse, ensuring that it remains within the optimal range for plant growth. It helps control heating and cooling systems by triggering ventilation fans when necessary, preventing temperature fluctuations that could harm plants.

3.     Soil Moisture Sensor: This sensor detects the amount of water in the soil, preventing both overwatering and underwatering. It automates irrigation systems by activating water pumps only when necessary, ensuring efficient water usage and healthier plant roots.

4.     Light Sensor: The light sensor measures the intensity of natural sunlight available in the greenhouse. When light levels drop below the required threshold, it signals artificial grow lights to turn on, ensuring plants receive adequate illumination for photosynthesis.

5.     IoT Integration: Enable remote monitoring and control through a mobile app or web dashboard.

6.     Smart Alerts & Notifications: Send alerts to users in case of critical environmental changes.

3     Project Scope

This project focuses on developing and implementing an IoT-based smart greenhouse management system. The core objective is to automate environmental controls within a greenhouse to optimize plant growth, reduce resource consumption, and minimize manual intervention. The system will monitor and control key environmental factors, including temperature, humidity, soil moisture, and light intensity.

3.1      Project Boundaries:

• The project will cover the design, development, and testing of the smart greenhouse system, including hardware and software components.
• The system will support remote monitoring and control capabilities via a user-friendly interface
• Integration with ThingSpeak will enable long-term data storage, analysis, and visualization.

Out of Scope:

• Physical construction of the greenhouse structure.
• Integration with existing agricultural machinery or legacy systems.
• Commercial deployment or mass production of the system.

Assumptions:

• Reliable Wi-Fi connectivity is available within the greenhouse environment.
• Sensors and actuators will perform according to their specified technical specifications.
• ThingSpeak API services will remain accessible and functional throughout the project.

3.2      Major Processes and Planned Workflow

The smart greenhouse system operates through the following major processes:

1. Data Acquisition:

• Sensors (light intensity, soil moisture, temperature, and humidity) collect real-time data from the greenhouse environment.

• The microcontroller processes the sensor readings and transmits them to the network layer via Wi-Fi.

1. Data Transmission and Storage:

• The network layer facilitates data transfer to the cloud platform (ThingSpeak).

• ThingSpeak stores the sensor data in designated channels for long-term analysis and visualization.

1. Automated Control:

• The system monitors environmental conditions and compares them against predefined thresholds.

• Based on these thresholds, the system automatically controls actuators (water pump, fan, LED lighting).

• If soil moisture falls below a threshold (e.g., 60%), the water pump activates.

• If temperature exceeds 30°C or humidity exceeds 85%, the fan activates.

• If light intensity falls below 25%, the high-intensity LEDs switch on.

1. Remote Monitoring and User Interaction:

• Greenhouse managers can monitor real-time conditions and adjust settings remotely via an alternative user interface.

• This interface provides alerts, historical data, and control options, enhancing the manager’s ability to manage the greenhouse from anywhere.

4 Project Novelty

Several smart greenhouse projects leverage IoT technology for environmental control and automation. Common features include sensor integration, remote monitoring, and automated adjustments of temperature, humidity, and irrigation. However, this project distinguishes itself through a combination of factors:

1. Focus on Open-Source Platforms:
   • Many existing projects rely on proprietary systems, incurring higher costs and limiting customization. This project emphasizes open-source platforms like ThingSpeak for data storage and analysis, reducing dependency on specific vendors and allowing for greater flexibility.
   • ThingSpeak provides a robust infrastructure for data collection, visualization, and analytics.
2. Emphasis on Scalability and Adaptability:
   • While some projects focus on small-scale setups, this project is designed to scale to larger operations. The modular design and reliance on cloud-based services make it easy to integrate additional sensors and actuators as needed.
   • The adaptability of the control system ensures that it can be tailored to the specific needs of different plant species or greenhouse configurations.
3. Optimized Resource Utilization:
   • The project integrates intelligent algorithms that optimize resource consumption (water, energy) based on real-time sensor data. This ensures that resources are used efficiently, reducing waste and costs.
4. User-Friendly Remote Interface:
   • Offers a streamlined user interface (Alternative app or web-based dashboard) that integrates monitoring, control, and alert functionalities. This simplifies the management of greenhouse operations and enables remote control from any location.
5. Data-Driven Decision Making:
   • ThingSpeak's analytic capabilities allow for data-driven decision-making, facilitating continuous optimization of greenhouse operations. By tracking historical data and identifying trends, greenhouse managers can fine-tune environmental settings to maximize plant growth and resource efficiency.

4.1      Advantages of This Project

The key advantages of this project compared to other smart greenhouse solutions are:

• Cost-Effectiveness: Utilizes open-source platforms to reduce upfront and ongoing costs.
• Scalability: Designed to accommodate both small and large greenhouse operations.
• Flexibility: It is Easily customizable to meet the specific needs of different plant species or greenhouse environments.
• Resource Efficiency: It integrates intelligent algorithms that optimize resource consumption.
• User-Friendliness: It provides a simplified user interface (via app or dashboard) for remote monitoring and control.
• Data-Driven Insights: Enable data-driven decision-making through ThingSpeak's analytic capabilities.

4.2      Need and Justification for the Project

The need for this project is driven by the limitations of traditional greenhouse management:

• Manual Intervention: Traditional greenhouse management relies heavily on manual adjustments of temperature, humidity, and irrigation, which is time-consuming and error-prone.
• Resource Waste: Inefficient control of resources leads to unnecessary waste of water, energy, and other inputs, increasing costs and environmental impact.
• Inconsistent Environmental Conditions: Fluctuations in environmental conditions can negatively impact plant growth and yields.
• Limited Remote Monitoring: Traditional systems lack the ability to monitor conditions remotely, making it difficult to respond to changing conditions in real-time.

This project addresses these limitations by:

• Automating Environmental Controls: Reducing the need for manual intervention and freeing up time for greenhouse managers to focus on other tasks.
• Optimizing Resource Utilization: Precisely controlling irrigation, ventilation, and lighting to minimize waste and reduce costs.
• Maintaining Consistent Conditions: Ensuring stable and optimal environmental conditions for plant growth.
• Enabling Remote Monitoring and Control: Providing greenhouse managers with the ability to monitor and adjust conditions from anywhere, at any time.

5 Microcontroller

Most IoT devices have to be small and work with relatively low energy consumption. This is particularly true for resource-constrained devices, which might operate far from a central system and use low-powered batteries to function. Such devices need something less heavy-duty than the type of processor found in a typical personal computer. For this, use microcontrollers.

Feature	Arduino	Raspberry pi
Power consumption	Low power consumption	High power consumption
Cost	Cheaper	Expensive
Ease of use	C-based IDE	Linux based
Sensor support	Supports analog and digital sensors	Need ADC for analog sensors

                        Table 3 Compare microcontrollers

5.1 Sensors

Sensors	Model	purpose
Soil Moisture Sensor	YL-69	Collects the moisture percentage of the soil
Temperature and Humidity Sensor	DHT-11	Collects data for the temperature and moisture of the environment
Light Intensity Sensor	Light Dependent Resistor (LDR)	Used to measure the light intensity

                         Table 4 Sensors in project

5.2 Actuators

• Water pump- In this system, the soil moisture sensor collects the moisture percentage of the soil once every 5 seconds, and the water pump is activated based on the moisture threshold. If the moisture percentage of the soil is more than 60%, the water pump is off, but if the moisture percentage is less than 60%, the water pump is activated for 500 ms.
• Fan control: A fan was installed in the greenhouse as a means of intaking air to control the temperature and humidity. The fan is programmed to turn on when certain conditions are met, which in this case are if either the temperature exceeds 30 degrees Celsius or if the humidity exceeds 85%.
• LED Lighting Control: When the light intensity falls below a threshold set at 25 %, the high-intensity LED swill switch on. This can provide the plants the ideal length of light each day,

5.3      Connectivity module

IoT modules come in various types, each designed for specific connectivity requirements and use cases. Communication modules focus on wireless connectivity, including Wi-Fi for high-speed local networks, Bluetooth for short-range device communication, cellular (2G/3G/4G/5G) for wide-area coverage, and LPWAN technologies like LoRaWAN and NB-IoT for long-range, low-power applications.

In this system, the Communication Module uses Wi-Fi to send data to the cloud.

5.4      Api and cloud

APIs are mechanisms that enable two software components to communicate with each other using a set of definitions and protocols. ThingSpeak is a platform providing various services exclusively targeted for building IoT applications. It offers the capabilities of real-time data collection, visualizing the collected data in the form of charts, and the ability to create plugins and apps for collaborating with web services, social networks, and other APIs.  

Blynk was designed for the Internet of Things. It can control hardware remotely, it can display sensor data, store data, visualize it, and do many other cool things. In this system, use Blynk app control conditions.

5.5 Project circuit Diagram

Rshon Shaked/sandbox