In greenhouse tomato cultivation, three primary methods of flower pollination exist: insect pollination, physical pollination by vibrating flowers, and artificial pollination using hormone-based chemicals. Insect pollination, the natural method, involves insects (e.g., honeybees) vibrating flowers to collect pollen and nectar. This paper proposes an alternate approach, using small drones to search and pollinate flowers in place of bees autonomously. We report field experiments conducted using these drone technologies. The drone must locate flowers ready for pollination. We developed an artificial intelligence (AI) image classification system (AI classifier) using machine learning to identify these flowers. Equipped with an AI classifier, the drone searches for flowers through autonomous flight and positioning technology. Upon identifying a suitable flower during its search, the drone makes contact to pollinate it. Integrating AI-based flower detection, autonomous flight control for flower search, and a pollination control device allows the drone to perform pollination. This study devises these technologies, implements them in a drone, and evaluates their effectiveness through a pollination experiment.

Network tomography is an inference technique for internal network characteristics from end-to-end measurements. In this letter, we propose a new network tomography scheme to classify communication links into lower or higher quality classes according to their link loss rates. The two-class classification is achieved by the estimation of link loss rates via compressed sensing, which is an emerging theory to obtain a sparse solution from an underdetermined linear system, with regarding link loss rates in the higher quality class as 0. In the proposed scheme, we implement compressed sensing with an ℓ₁-ℓ₂ optimization, where the cost function is defined as a sum of ℓ₁ and ℓ₂ norms with a mixing parameter, which enables us to control the threshold between the lower and higher quality classes.

In this study, we realized a relay network using drones and analyzed the impact of the sway angle of a drone’s attitude on communication in a windy flight environment. Drones in flight act as radio relay stations and communication among them is performed using radio equipment mounted on board. In a windy environment, a directional antenna is used for relay communication among them to avoid interference caused by the spread of radio waves in space and extend the relay distance. However, when wind occurs during flight, the flying attitude of the drone inclines, which causes the beam of the antenna to sway and the communication link to be disconnected, leading to a decrease in the transmission speed. In this study, we statistically evaluated the pitch, yaw, and roll axes of a drone through wind tunnel experiments. Furthermore, the pattern of the swing angle of the drone with respect to the wind speed was investigated using computer simulations to analyze the fluid dynamics and theoretically analyze the swing of the drone. Based on these results, the transmission speed when using a directional antenna was calculated. When the wind speed was 6.0 m/s, the pitch axis deflection angle of the drone was 13${}^{\circ }$ at maximum, and the average transmission speed decreased by 33.3 Mbps. In this study, it was found that in communication between drones due to the wind, the transmission efficiency decreased depending on the sway angle of the aircraft.

In this paper, we consider the broadcast storm problem in dense wireless ad hoc networks where interference among densely populated wireless nodes causes significant packet loss. To resolve the problem, we apply randomized network coding (RNC) to the networks. RNC is a completely different approach from existing techniques to resolve the problem, and it reduces the number of outstanding packets in the networks by encoding several packets into a single packet. RNC is a kind of linear network coding, and it is suited to wireless ad hoc networks because it can be implemented in a completely distributed manner. We describe a procedure for implementing the wireless ad hoc broadcasting with RNC. Further, with several simulation scenarios, we provide some insights on the relationship between the system parameters and performance and find that there is the optimal length of coding vectors for RNC in terms of packet loss probability. We also show a guideline for the parameter setting to resolve the broadcast storm problem successfully.

We consider a UAV (Unmanned Aerial Vehicle) relay network whereby each UAV senses data and forwards it to dedicated ground stations by means of multi-hop relaying. In particular, we focus on a UAV relay network with a simple yet realistic linear topology for which we propose an adaptive direction control scheme to achieve a high throughput performance. In the proposed scheme, each UAV, equipped with multiple directional antennas, selects either the Decode-and-Forward (DF) straight relaying method or the orthogonal relaying method, for full-duplex data transfer, i.e., data is transmitted and received simultaneously on the same frequency, but at different antennas. The originality of our proposed method is to make each UAV rotate relatively to the position of its neighbouring UAVs, in order to optimize its antenna radiation direction, according to the selected relaying method. The key advantage of the proposed method is that signal direction can be controlled without the need of heavy adaptive signal processing as in conventional beamforming techniques. In order to clarify the decision parameters for selecting a relaying method, we first evaluate the throughput performance of the two-hop relay network under the severe interference conditions of UAV networks, and next, propose a procedure for selecting a multihop relaying method. Numerical experiments show that the proposed scheme enables to achieve a high throughput performance, with low computational costs.

In this paper, we propose an uplink multiuser-multiple input multiple output (MU-MIMO) cooperative retransmission control scheme for the reliable and efficient communication of autonomous unmanned aerial vehicles (i.e., flight communication and drone-to-drone communication). This scheme is a key element in the design of a drone-based ad-hoc network. Because drone relay transmission operates in the air, flexible wireless relay networks over large areas can be achieved without interference from multipath signals caused by buildings and obstacles in ground-based communication. However, two main challenges exist. First, the relay transmission system occupies bandwidth every time the drone relays information. Therefore, because the radio channel is shared by multiple relay stations, the throughput is greatly reduced. To improve throughput, it is better to transmit using the minimum number of relay stations. Ultimately, long-distance direct transmission is the best. The other issue is a direct result of the first issues solution: the propagation loss increase when relaying information directly over a long distance. Moreover, because the frequency of interference waves from the ground increases, transmission signal errors are an important issue. To solve this issue, a transmission scheme to reduce errors is required. The scheme proposed in this study achieves high transmission reliability and efficiency even under high transmission error conditions. The results of a computer simulation reveal that the proposed method achieves a direct transmission throughput that is 1.5 times better than that of a conventional scheme. It is also shown that the proposed scheme requires only about three stations to achieve acceptable results.