The population increases at an exponential rate as human society advances, and pollution is increasingly depleting the availability of resources such as water and land. All these problems are thought to require the use of smart agriculture. By reducing use of chemical fertilizers and pesticides, smart agriculture could mitigate land pollution and increase the sustainability of agricultural practices while also greatly enhancing the agro-ecological environment, yield, and quality of crops. The steps to make agriculture smart are made possible through data and communication technology, which helps with automatic operation and cultivation. Moreover, advances in wireless communication protocols will bring agriculture to a more intelligent stage. This study provides an overview of IoT technology and its application in the smart agriculture industry to make crop production automatic and intelligent by assessing their architecture (IoT devices, communication technologies, and processing), their applications, and research timelines. The communication protocols that have established uses in agriculture are reviewed first in this article. Various wireless communication protocols such as WiFi, ZigBee, SigFox, LoRa, RFID, NFMI, Terahertz, and NB-IoT were summarized, and their applications in various fields were also studied. These protocols in smart agriculture can effectively and efficiently address environmental data, water saving, monitoring of animal behavior, accuracy, power efficiency, cost reduction due to low power consumption, accuracy, wide transmission, simple in operation and cost effective. The most commonly used microcontrollers are Arduino (to develop autonomous machines), Raspberry Pi (to store data), and 8-bit microcontroller (to process data). In addition, it is important to take advantage of modern communication technology to enhance crop production. This study also examines the future opportunities and trends for IoT applications in smart agriculture, along with the ongoing challenges and issues that need addressing. Furthermore, it provides crucial insights and guidance for future research and the development of IoT solutions. These advancements aim to improve agricultural productivity and quality while facilitating the transition to a more sustainable agroecological future.

Weed control in agricultural systems is of the utmost importance. Weeds reduce crop yields by up to 30% to 40%. Different methods are used to control weeds, such as manual, chemical, mechanical, and precision weed management. Weeds are managed more effectively by using the hand weeding method, which nevertheless falls short due to the unavailability of labor during peak periods and increasing labor wages. Generally, manual weeding tools have higher weeding efficiency (72% to 99%) but lower field capacity (0.001 to 0.033 hm²/h). Use of chemicals to control weeds is the most efficient and cost-effective strategy. Chemical weedicides have been used excessively and inappropriately, which has over time resulted in many issues with food and environmental damage. Mechanical weed control improves soil aeration, increases water retention capacity, slows weed growth, and has no negative effects on plants. Mechanical weed management techniques have been gaining importance recently. Automation in agriculture has significantly enhanced mechanization inputs for weed management. The development of precision weed management techniques offers an efficient way to control weeds, contributing to greater sustainability and improved agricultural productivity. Devices for agricultural automated navigation have been built on the rapid deployment of sensors, microcontrollers, and computing technologies into the field. The automated system saves time and reduces labor requirements and health risks associated with drudgery, all of which contribute to more effective farm operations. The new era of agriculture demands highly efficient and effective autonomous weed control techniques. Methods such as remote sensing, multispectral and hyperspectral imaging, and the use of robots or UAVs (drones) can significantly reduce labor requirements, enhance food production speed, maintain crop quality, address ecological imbalances, and ensure the precise application of agrochemicals. Weed monitoring is made more effective and safer for the environment through integrated weed management and UAVs. In the future, weed control by UAV or robot will be two of the key solutions because they do not pollute the environment or cause plant damage, nor do they compact the soil, because UAV sprays above the ground and robotic machines are lighter than tractor operated machines. This paper aims to review conventional, chemical, mechanical, and precision weed management methods.

Insect infestation attacks in agricultural ecosystems are becoming more common because of global warming as well as farmland environmental circumstances, necessitating the development of new crop production technology. Pesticide application is one of the most common strategies for protecting the entire growing period of plants or shrubs against pests and pathogens in farms. The rapid, effective, and profitable application of plant control substances via unmanned aerial vehicle (UAV) crop spraying is anticipated to be a key new technique. When compared to ground spraying, UAV spraying saves chemicals, water, time, does not damage crop plants or balls of crop, and does not create soil compaction. When using UAV, pesticide drift and deposition must be managed in order to use pesticides safely, effectively, and efficiently. This paper focuses on agrochemical spraying by unmanned aerial vehicles and the key parameters that influence spray effectiveness, such as the operating parameters of nozzle type, flying speed, flight height, type of nozzle, and type of UAV model, for reducing drift and increasing application efficiency. The multirotor UAV is most suitable for spraying due to its fast operation, safety, not requiring a runway for takeoff and landing, and lower cost as compared to fixed-wing and VTOL. UAVs can also be used for crop disease identification, soil health monitoring, livestock monitoring, field mapping, etc. This paper aims to review the development of various UAV models, optimization of operating parameters, effect of nozzle on UAV spraying, characterization of droplet deposition, drift reduction technology, UAV-based remote sensing for plant protection, and cost comparison of UAV to conventional ground sprayer.