IoT is a revolutionary technology that shows the future of computing and communications and using large scale IoT platforms it is easy to process various number of sensor data. IoT refers to network of objects with wireless technology. IoT platforms are used to process ,analyse the data and produce smart solutions in a short time. This article is to put transmission between wireless sensors and internet for smart agriculture. GPS, RFID,3G, GPRS, geomactics , cloud computing are included with the internet of things are to be focused in order to develop Smart Agriculture.
Real time detection. By scripting on RaspberryPi, the monitoring system can get the features like humidity, moisture, light , temperature where the sensors like humidity sensor (RHT03) ,soil moisture sensors ,temperature sensors and PIR sensors can be used to detect the changes in moisture, temperature and light conditions in and around the farm and results are obtained and plotted in graphical form based sheets.
Big data analyses are performed to maintain best crop, good production and safe farming.
Table of Contents
1. Introduction
2. RaspberryPi interface
3. Related work
4. Structure of Wireless monitoring framework for smart farming
5. Mosquitto MQTT Broker
6. IoT security
7. IoT communication Models
8. Zigbee Coordinator
9. Wireless range of sensor devices
10. Smart farming generic life cycle
11. Decision modules adaptive software architecture
12. Smart farming challenges
13. ROLE OF THE INTERNET OF THINGS IN THE AGRICULTURAL
14. Smart farming needs
15. Schematic of the circuit
16. Conclusion
Objectives and Topics
The primary objective of this work is to explore and implement Internet of Things (IoT) technologies to enhance smart agriculture by enabling real-time monitoring and data-driven decision-making. The research investigates how IoT gateways, wireless sensor networks, and cloud-based platforms can be integrated to optimize crop yields, improve resource efficiency, and address the complexities of modern farming.
- Integration of IoT sensors (humidity, temperature, light, moisture) with Raspberry Pi for real-time farm monitoring.
- Evaluation of MQTT communication protocols for reliable data transmission in agricultural environments.
- Analysis of layered architectures for smart farming, including data management and cloud-based decision support.
- Identification of technical challenges, such as interoperability, data standardization, and software development needs.
- Security considerations for decentralized IoT gadgets in smart farming ecosystems.
Excerpt from the Book
1. Introduction
The improvement of profoundly accurate embedded sensors for measuring the conditions in farms and fields enables the accurate and precision agriculture. Due to this a farmer can enhance the productivity and expand yields and profitability and can diminish the ecological impression, by methods, for example, more efficient water system, targeted, more exact utilization of composts and pesticides for crops, and in addition nourishment and anti-toxins for animals. This precision agriculture enables the smart agriculture.
The Internet of Things permits the sensors to be perceived and guarded remotely more than a current system foundation, this makes more clear-cut assimilation between the physical world and Personal Computer based platforms. Therefore , it brings about enhanced efficiency, accuracy and economic advantages.
This will give the premise to numerous new applications, for example, energy observing, transport wellbeing frameworks or building security. This vision will without a doubt change with time, particularly as cooperative energies between Identification Technologies, Wireless Sensor Networks, and Nanotechnology will empower various propelled applications. Imaginative utilization of advancements, for example, RFID, NFC, ZigBee and Bluetooth, are adding to make an incentive for partners of IOT.
Summary of Chapters
1. Introduction: Introduces the importance of IoT in precision agriculture, emphasizing its role in improving efficiency and productivity.
2. RaspberryPi interface: Describes the hardware interfacing of Raspberry Pi with various sensors to enable smart monitoring.
3. Related work: Discusses existing frameworks for IoT in urban settings and their applicability to smart farming needs.
4. Structure of Wireless monitoring framework for smart farming: Outlines the layered architecture required for managing smart agriculture data and applications.
5. Mosquitto MQTT Broker: Evaluates the MQTT protocol for efficient and dependable data transmission in rural and agricultural settings.
6. IoT security: Addresses the critical security challenges inherent in transitioning to decentralized smart IoT gadgets.
7. IoT communication Models: Explores different communication models like device-to-cloud and device-to-gateway for agricultural IoT systems.
8. Zigbee Coordinator: Details the role of ZigBee hubs and coordinators in establishing low-power, short-range sensor networks.
9. Wireless range of sensor devices: Analyzes how distance requirements dictate the choice of communication technologies like RFID, Bluetooth, or LPWAN.
10. Smart farming generic life cycle: Explains the lifecycle of data and events, from sensing to cloud-based management and decision planning.
11. Decision modules adaptive software architecture: Discusses the need for adaptive cloud-based Decision Support Systems (DSS) tailored for specific farming operations.
12. Smart farming challenges: Identifies key hurdles including data handling, interoperability, standardization, and regional cultural differences.
13. ROLE OF THE INTERNET OF THINGS IN THE AGRICULTURAL: Examines how IoT helps purify the material market and reduce the burden on farmers.
14. Smart farming needs: Lists essential resources for building an IoT farming system, such as cloud hosting and data service management.
15. Schematic of the circuit: Provides a visual overview of how sensors are circuited with controllers like Arduino.
16. Conclusion: Summarizes the findings and potential for future advancements in smart farming technologies.
Keywords
Internet of Things, Big data analytics, Cloud computing, sensors, Smart farming, geomatics, Raspberry Pi, MQTT, ZigBee, Precision agriculture, Wireless sensor network, Data interoperability, Decision support system, Infrastructure, Automation.
Frequently Asked Questions
What is the core focus of this research?
The work focuses on the integration of IoT technologies into agriculture to enable real-time monitoring and precision farming practices.
What are the primary themes discussed?
The main themes include sensor hardware integration, communication protocols like MQTT, cloud-based data management, and the challenges of standardization in agriculture.
What is the primary objective of the proposed framework?
The primary objective is to create an efficient, scalable, and adaptable monitoring system that helps farmers increase productivity while minimizing resource consumption.
Which scientific methods are utilized?
The study employs a technical design approach, utilizing Raspberry Pi and Arduino interfaces, alongside network analysis of protocols like MQTT and ZigBee to evaluate data transmission effectiveness.
What is covered in the main body of the work?
The main body details the architectural layers of IoT systems, security requirements, specific communication models, and the practical challenges of deploying these systems in a farming environment.
Which keywords characterize this document?
Key terms include IoT, Smart Farming, Big Data, Precision Agriculture, Raspberry Pi, and Wireless Sensor Networks.
How does the Raspberry Pi facilitate the smart farming process?
It acts as a central hub that interfaces with various environmental sensors, processes the incoming data, and transmits it to a web server or cloud for analysis.
What is the significance of the "MQTT Broker" in this context?
The MQTT broker is used as a lightweight messaging protocol to ensure reliable and low-bandwidth communication of intermittent sensor data from remote agricultural machinery.
Why are interoperability and standardization highlighted as major challenges?
Interoperability is crucial because different farming equipment, software, and data sources often lack common communication protocols, which increases complexity and costs for the end-user.
- Quote paper
- Sai Charan (Author), 2017, Enabling Innovation in Agriculture and Improving Access to Key Service by IOT (Internet of Things) Gateway, Munich, GRIN Verlag, https://www.grin.com/document/385502
