Presently in agriculture, there is much ample scope for drone and UAS (Unmanned Aircraft System) development. Because of their low cost and small size, these devices have the ability to help many developing countries with economic prosperity. The entire aggregation of financial investments in the agricultural area has increased appreciably in recent years. Sooth to say, agriculture remains a massive part of the world’s commercial growth, and due to some complications, the agriculture fields withstand massive losses. Pets and destructive insects seem to be the primary reasons for certain degenerative diseases. It minimizes the potential productivity of the crops. For increasing the quality of the plants, fertilizers and pesticides are appropriately applied. Using UAVs (Unmanned Aerial Vehicles) for spraying pesticides and fertilizing materials is an exuberant contraption. It adequately reduces the rate of health dilemma and the number of workers, which is quite an impressive landmark. Willing producers are also adopting UAVs in agriculture to soil and field analysis, seed sowing, lessen the time and costs correlated with crop scouting, and field mapping. It is rapid, and it can sensibly diminish a farmer’s workload, which is significantly a part of the agricultural revolution. This article aims to proportionally represent the concept of agricultural purposed UAV clear to the neophytes. First, this paper outlines the harmonic framework of the agricultural UAV, and then it abundantly illustrates the methods and materials. Finally, the article portrays the outcome.

The problem of air pollution is an increasingly serious worldwide. Therefore, in order to better monitor the gas components in the atmosphere, the design of a gas monitoring terminal based on a quadrotor UAV, including software and hardware design, is hereby carried out. Besides, a pump-suction series cavity is designed to reduce the influence of airflow disturbance on the UAV, which is verified to possess a certain anti-interference ability through Computational Fluid Dynamics(CFD) simulation experiments. In addition, a linear regression algorithm is used for sensor calibration and a polynomial piecewise regression method is used for temperature compensation. The experimental results show that the R² of the model reaches 0.9981, the fitting degree is rather high, and the output is closer to the real gas concentration value after calibration. At the same time, the temperature compensation parameters are determined, which considerably improves the accuracy of the entire hardware terminal. Finally, the vehicle exhaust monitoring experiment is conducted, and the experimental results show that this scheme can successfully detect the exhaust position of the vehicle exhaust under the interference of the downwash flow of the UAV, thereby proving the reliability and accuracy of the monitoring terminal.

Human activity recognition (HAR) has been increasingly used in medical care, behavior analysis, and entertainment industry to improve the experience of users. Most of the existing works use fixed models to identify various activities. However, they do not adapt well to the dynamic nature of human activities. We investigated the activity recognition with postural transition awareness. The inertial sensor data was processed by filters and we used both time domain and frequency domain of the signals to extract the feature set. For the corresponding posture classification, three feature selection algorithms were considered to select 585 features to obtain the optimal feature subset for the posture classification. And We adopted three classifiers (support vector machine, decision tree, and random forest) for comparative analysis. After experiments, the support vector machine gave better classification results than other two methods. By using the support vector machine, we could achieve up to 98% accuracy in the Multi-class classification. Finally, the results were verified by probability estimation.