Internet of Things for Crop Farming: A Review of Technologies and Applications
Abstract
:1. Introduction
2. Methods
2.1. Eligibility Criteria
2.2. Information Sources
2.3. Search Strategy and Selection Process
2.4. Data Analysis and Synthesis
2.5. Findings
3. Discussion
3.1. IOT Technologies for Crop Farming
3.1.1. Wireless Sensors
3.1.2. Communication and Networks Protocols
3.1.3. Cloud Computing/Fog Computing
3.1.4. Cyber Security
3.2. IOT Applications
3.2.1. Cloud Computing/Fog Computing
3.2.2. Crop growth and Yield Enhancement
3.2.3. Irrigation Systems
3.2.4. Weed Detection and Removal
3.2.5. Plant Health Monitoring
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Crop Stage | Intruders | Effects | ||||
---|---|---|---|---|---|---|
Rodents | Insects/Pests | Livestock | Wildlife | Birds | ||
Seed Planting of germination | ✓ | ✓ | ✓ | Poor Germination | ||
Few leaves to stem elongation | ✓ | ✓ | ✓ | Poor Growth | ||
Grain, Fruit, Vegetable filling/ripening | ✓ | ✓ | ✓ | ✓ | Possible destruction poor produce |
Ref. | Intruder Detected | Crop | Technology | Control Measures | |
---|---|---|---|---|---|
[30] | Borer insects | Tomato fruit | Camera, Robotic car, Hardware/Processor (Intel i3 32-bit core processor), Software operating system, (Microsoft Azure), Software application (Java) | Pesticides spray | detection |
[31] | Locust, grasshopper | Hardware tools—(1) Node MCU (2) Raspberry Pi, (3) Relay module, (4) Sensors—(i) DHT11 temperature and humidity sensor, (ii) FC08 Resistive Soil Sensor Output devices—(1) water pump, (2) Vacuum pump, (3) Pestcide Pump, (4) UV light, (5) Speaker Software tools—(1) Arduino IDE, (2) Android Studio, (3) Python IDE, (4) ThingSpeak | Instantly kill locust using Malathion and Chlorpyrifos spray UV generator—kill locusts by emitting UV radiation | monitoring | |
[32] | Litchi stink bugs (Tessaratoma papillosa) | Litchi Tress | Hardware architecture—(1) Arduino Nano, (2) sensors: (i) GY-30 for light, (ii) YL-69 for soil, (iii) DHT22 for temperature and humidity, and (iv) BMP180 for atmospheric pressure, (3) DS3231 module, (4) Raspberry Pi 4, (5) LoRa transmission module. Transmission Mechanism: (i) LoRa—long-range transmission (ii) WIFI and Bluetooth—short-range transmission | ||
[33] | Red palm weevil (RPW) larvae | Date palm trees | Combination of IoT platform1sensing sound device, (1) cloud services (2) global positioning system (GPS) and (3) deep learning MixConvNet classifier | detection | |
[34] | Insect/pest | IoT technologies passive infrared (PIR) sensors | Spray pheromones—a spray that manipulates insects’ physiological communication pathways, male cannot find female | ||
Birds and rodents | IoT technologies passive infrared (PIR) sensors | Repel intruders from entering the field. | |||
[35] | Pest | Rice | Internet of Things (IoT) assisted Unmanned Aerial Vehicle (UAV) based | Detection and identification | |
[36] | Lepidoptera species: (moths and butterflies) | Tomato leaf | Optical sensors emitter-receiver per layer. e electronic funnel trap (e-funnel)—optical counter, emitter, receiver, wireless communication, LoRa radio protocol, pair of 8 emitting LEDs and 8 receiving photodiodes | Traps the species into a funnel with sex pheromone dispenser | Detection of a new infestation, Monitoring insects’ population size |
[37] | Insect/Pests i.e whiteflies, aphids and moths (fully grown EFSB). | eggplant | IoT technology (SSD Lite-MobileNet COCO v2. SDD-MobileNet model, Raspberry Pi), plus Deep and machine learning—TensorFlow and a camera | Detection, Identification, Counting | |
[38] | Rodents, grasshoppers and locusts, lacewings and moths | Crop field | IoT technology with ultrasonic sound emitter | Ultrasonic sounds: (1) confuse the pests and it affects their brain and nervous system. (2) reduces mating and reproduction (3) repel | repel |
[39] | Buffaloes, cows, goats, birds | Crop field | IoT technology—PIR and ultrasonic sensors | The sound is played to divert the animal. | repel |
[40] | Insects and animals | Crop field | IoT technology—Ultrasonic insects and animal Repeller that is embedded with Piezo-Electric Buzzer, an IR-Sensor and ATmega16 Microcontroller. | Creating ultrasonic sound drives away the intruder. | repel |
[41] | Wild animals | Crop field | IoT technology—Ultrasonic sensors Camera, E-vehicle, Node MCU Microcontroller | Detects, image capture, monitor | |
[42] | Insects | Crop field | Hardware-raspberry-pi, infrared sensor, camera, insect chamber, tank Software layers—Arch linux, Python, Compression algorithms, network, Cloud layer—microservices, image processing Machine learning layer- tensor flow SciKit-Learn, NN Classifier, Naïve Bayes classifier | Detect pests of fields using a system to attract insects by creating several stimuli (chromatic, food, sexual, and UV light). takes a picture of the insect and uses Cloud Based Machine Learning (ML) algorithms to classify the image, then checks if the insect is dangerous to the crops or not. | Detects, image capture, |
[43] | Animals or Humans, | Crop field | HC-SR04 Ultrasonic sensor, Arduino Uno Board ATmega328P. GSM 900A, Piezo Buzzer | Ultrasonic sensor to detect an intruder and GSM 900A is used to send a notification to farmer | Detection |
[44] | Pests such as beetles, bugs, moth, and rodents including rats, squirrels, mouse, rabbits | paddy, wheat, cotton | IoT Technology: Passive Infrared (PIR) sensor, Image processing, Acoustic sensor, Microcontroller, Ultrasonic generator. | Detect the presence of insect Capture images of the pest Generate ultrasonic waves | Detect and repel |
[45] | Wild animals like monkeys, stray animals especially cows and buffaloes, wild dogs, nilgais, bisons, elephants, deer, wild pigs, and even birds | fruit orchards | IoT Technology: passive infrared sensor (PIR sensor-based motion detectors.), Node MCU, LCD, Arduino, PIR Sensor, APR9600. | Generate sound to drive the intruder away. Sends a message to the farmers, takes the safety precautions | Detects and repel |
[46] | Birds | Pearl, Millet, sorghum, maize | IoT Technology: motion detection using PIR(Passive Infrared) based motion detectors, Wemos D1: The Wemos D1 is an ESP8266 WiFi-based board that uses the Arduino layout with an operating voltage of 3.3 V, PIR Motion Detector Sensor, MicroSD Card, MP3 Module, Audio Amplifier, Megaphone or any other sound-emitting device, External Battery: | Detects motion Generate sounds of the predator which will drift the birds away from the field | Detects and repel |
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Ndjuluwa, L.N.P.; Adebisi, J.A.; Dayoub, M. Internet of Things for Crop Farming: A Review of Technologies and Applications. Commodities 2023, 2, 367-381. https://doi.org/10.3390/commodities2040021
Ndjuluwa LNP, Adebisi JA, Dayoub M. Internet of Things for Crop Farming: A Review of Technologies and Applications. Commodities. 2023; 2(4):367-381. https://doi.org/10.3390/commodities2040021
Chicago/Turabian StyleNdjuluwa, Leokadia N. P., John A. Adebisi, and Moammar Dayoub. 2023. "Internet of Things for Crop Farming: A Review of Technologies and Applications" Commodities 2, no. 4: 367-381. https://doi.org/10.3390/commodities2040021