Human movement tracking is useful in a variety of areas, such as search-and-rescue activities. CCTV and IP cameras are popular as front-end sensors for tracking human motion; however, they are stationary and have limited applicability in hard-to-reach places, such as those where disasters have occurred. Using a drone to discover a person is challenging and requires an innovative approach. In this paper, we aim to present the design and implementation of a human motion tracking method using a Tello EDU drone. The design methodology is carried out in four steps: (1) control panel design; (2) human motion tracking algorithm; (3) notification systems; and (4) communication and distance extension. Intensive experimental results show that the drone implemented by the proposed algorithm performs well in tracking a human at a distance of 2–10 m moving at a speed of 2 m/s. In an experimental field of the size $95\times 35{\mathrm{m}}^2$, the drone tracked human motion throughout a whole day, with the best tracking results observed in the morning. The drone was controlled from a laptop using a Wi-Fi router with a maximum horizontal tracking distance of 84.30 m and maximum vertical distance of 13.40 m. The experiment showed an accuracy rate for human movement detection between 96.67 and 100%.

Energy is a main concern in the design and deployment of Wireless Sensor Networks because sensor nodes are constrained by limitations of battery, memory, and a processing unit. A number of techniques have been presented to solve this power problem. Among the proposed solutions, the data compression scheme is one that can be used to reduce the volume of data for transmission. This article presents a data compression algorithm called Differential Run Length Encryption (D-RLE) consisting of three steps. First, reading values are divided into groups by using a threshold of Chauvenet’s criterion. Second, each group is subdivided into subgroups whose consecutive member values are determined by a subtraction scheme under a K-RLE based threshold. Third, the member values are then encoded to binary based on our ad hoc scheme to compress the data. The experimental results show that the data rate savings by D-RLE can be up to 90% and energy usage can be saved more than 90% compared to data transmission without compression.

This paper presents a speed testing platform designed to evaluate Thailand’s Internet broadband network experience. The platform measures internet speed at the ONT (Optical network terminal) as a signal source for the operator (or ISP) and the connected internet device at the user’s accommodation (fixed broadband internet). Scenario tests were conducted involving four major broadband network operators in Thailand, with our application collecting data from 30 devised-based operators and 200 internet users, resulting in a dataset of 25,000 records. The primary focus of our study was on assessing download and upload speeds, as well as latency. The proposed system was deployed in 8 provinces east of Thailand over two months. Results indicate that the Download Percentage Average (DPA) was 64.30%, while the Upload Percentage Average (UPA) was 71.84%. The average ping and jitter were 11.82 ms and 16.53 ms, respectively. Analysis revealed variations in average speed and latency values across different areas and period times, underscoring the efficacy of our system. Our proposed platform could serve NBTC as a central platform for evaluating future broadband internet services in Thailand.

This study proposes a framework for a geospatial internet speed test platform, specifically designed to assess the broadband network experience in Thailand. The novelty of this research lies in its comprehensive approach to broadband internet quality assessment, uniquely measuring internet performance from ISPs sources to end-users using custom-designed reTerminal hardware devices based on Raspberry Pi 4. Tests were conducted involving four major broadband service providers. Data were collected from 30 speed test devices, which were installed at the source of each service provider network, and 200 internet user devices. The total number of data records collected was 25,000. The results indicated that the Download Percentage Average was 64.30%, while the Upload Percentage Average was 71.84%. The average latency and jitter were 11.82 ms and 16.53 ms, respectively. All speed test parameters at the source of the ISPs network were found to reach almost 100% compared to the speed test network devices of the ISPs. This means that ISPs provide internet quality according to the standards set by the NBTC. These results can assist the NBTC for setting relevant policies or strategies to improve the quality of broadband internet services at user's sites.