Intelligent Agriculture System Based on LoRa and Qt Technology

Liu, Jing; Yao, Wenxi

doi:10.1109/ccdc.2019.8833476

Cited by 20 publications

(7 citation statements)

References 8 publications

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“…Extended transmission range is one of the benefits of low power wide area networks (LPWAN). Comparing IoT communication technology to current wireless communication technologies, the former offers greater coverage capacity, lower costs, and lower power usage [24]. The purpose of this study is to address the long-distance communication needs of intelligent agriculture systems by establishing an information transmission system using a long-range (LoRa) wireless network and connecting it to an upper computer system and sensor control system.…”

Section: Design Of Iot Stingless Beementioning

confidence: 99%

A review on internet of things-based stingless bee's honey production with image detection framework

Rohafauzi,

Kassim,

Ja’afar

et al. 2024

IJECE

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Honey is produced exclusively by honeybees and stingless bees which both are well adapted to tropical and subtropical regions such as Malaysia. Stingless bees are known for producing small amounts of honey and are known for having a unique flavor profile. Problem identified that many stingless bees collapsed due to weather, temperature and environment. It is critical to understand the relationship between the production of stingless bee honey and environmental conditions to improve honey production. Thus, this paper presents a review on stingless bee's honey production and prediction modeling. About 54 previous research has been analyzed and compared in identifying the research gaps. A framework on modeling the prediction of stingless bee honey is derived. The result presents the comparison and analysis on the internet of things (IoT) monitoring systems, honey production estimation, convolution neural networks (CNNs), and automatic identification methods on bee species. It is identified based on image detection method the top best three efficiency presents CNN is at 98.67%, densely connected convolutional networks with YOLO v3 is 97.7%, and DenseNet201 convolutional networks 99.81%. This study is significant to assist the researcher in developing a model for predicting stingless honey produced by bee's output, which is important for a stable economy and food security.

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Section: Design Of Iot Stingless Beementioning

confidence: 99%

A review on internet of things-based stingless bee's honey production with image detection framework

Rohafauzi,

Kassim,

Ja’afar

et al. 2024

IJECE

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“…The most common LPWAN protocol, in SF, is LoRaWan, an open access protocol that uses LoRa technology. To set up a LoRaWan network, one can use a microcontroller that supports a LoRa module such as Arduino Uno that works with LoRa/GPS shield [160] or the STM32F103 that is compatible with Lora module Ra01 [161]. Setting up the LoRa network requires calibration of the sender and receiver antenna gain [160].…”

Section: ) M2g Communication Protocolsmentioning

confidence: 99%

“…Another drawback of LPWAN is the risk of data collision when two nodes are sending data simultaneously. This challenge has been addressed in [161] by allocating independent time slots for transmission for each node. The solutions proposed to overcome LPWAN limitations increases power consumption; Hence, optimization is needed between power consumption, coverage area, and data rate.…”

Section: ) M2g Communication Protocolsmentioning

confidence: 99%

Technologies Driving the Shift to Smart Farming: A Review

Elbeheiry

Balog

2023

IEEE Sensors J.

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As today's agriculture industry is facing numerous challenges, including climate changes, encroachment of the urban environment and lack of qualified farmers, there is a need for new practices to ensure sustainable agriculture and food supply. Consequently, there is an emphasis on upgrading the farming practices by shifting towards Smart Farming (SF) -utilizing advanced information and communication technologies to improve the quantity and quality of the crop with minimal labor interference. SF has gained lots of interest in recent years utilizing a variety of technological innovations in the field, which imposes a challenge on farmers and technology integrators to identify the suitable technologies and best practices for a particular application. This paper provides a survey of the most recent SF scientific literature to identify common practices toward technology integration, challenges, and solutions. The survey was conducted on 588 papers published on the IEEE database following Cochrane methods to ensure appropriate analysis and interpretation of results. The papers' contributions were analyzed to identify necessary technologies that constitute SF, and consequently, research themes were identified. The identified themes are sensors, communication, big data, actuators and machines, and data analysis. Besides presenting an in-depth analysis of each identified theme, the paper discusses integrating more than one technology in systems to achieve independency. The most common SF systems are remote monitoring, autonomous, and intelligent decision-making systems.

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“…Based on these traits and contemplating the needs of agricultural applications, ZigBee can perform a significant role, particularly for the environments of greenhouses that often require short-range transmissions. During different parameter observations, actual-time information from the sensor nodes is transmitted to the terminal server via Zigbee [107,108]. For applications such as fertilizers and irrigation, the ZigBee module can be used for transmission, such as in drip irrigation, to check the soil moisture content.…”

Section: Zigbeementioning

confidence: 99%

Current Progress and Future Prospects of Agriculture Technology: Gateway to Sustainable Agriculture

et al. 2021

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The agricultural industry is getting more data-centric and requires precise, more advanced data and technologies than before, despite being familiar with agricultural processes. The agriculture industry is being advanced by various information and advanced communication technologies, such as the Internet of Things (IoT). The rapid emergence of these advanced technologies has restructured almost all other industries, as well as advanced agriculture, which has shifted the industry from a statistical approach to a quantitative one. This radical change has shaken existing farming techniques and produced the latest prospects in a series of challenges. This comprehensive review article enlightens the potential of the IoT in the advancement of agriculture and the challenges faced when combining these advanced technologies with conventional agricultural systems. A brief analysis of these advanced technologies with sensors is presented in advanced agricultural applications. Numerous sensors that can be implemented for specific agricultural practices require best management practices (e.g., land preparation, irrigation systems, insect, and disease management). This review includes the integration of all suitable techniques, from sowing to harvesting, packaging, transportation, and advanced technologies available for farmers throughout the cropping system. Besides, this review article highlights the utilization of other tools such as unmanned aerial vehicles (UAVs) for crop monitoring and other beneficiary measures, such as optimizing crop yields. In addition, advanced programs based on the IoT are also discussed. Finally, based on our comprehensive review, we identified advanced prospects regarding the IoT, which are essential tools for sustainable agriculture.

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Intelligent Agriculture System Based on LoRa and Qt Technology

Cited by 20 publications

References 8 publications

A review on internet of things-based stingless bee's honey production with image detection framework

A review on internet of things-based stingless bee's honey production with image detection framework

Technologies Driving the Shift to Smart Farming: A Review

Current Progress and Future Prospects of Agriculture Technology: Gateway to Sustainable Agriculture

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