RSSI Values Research Articles

Performance of LoRa SX1278 Using Yagi Antenna

This study examines the use of Yagi antennas to extend the LoRa SX1278 transceiver's range, focusing on enhancing communication distance and reducing signal loss. LoRa, a low-power wireless technology, enables long-distance transmission ideal for sensor data, reaching up to 15 km in rural areas and 1-5 km in urban environments. By adjusting impedance, the Yagi antenna improves LoRa signal range and quality by focusing transmission directionally, reducing interference. The test results show that the yagi antenna has better coverage and signal strength than the spring antenna. Testing horizontal conditions with 3 different locations shows that antenna design greatly affects the transceiver of data. The Yagi antenna with modified impedance has the ability to transmit the farthest distance of 6250 meters. Horizontal testing with a fairly short distance is not too significant a difference in the rssi value of the two antennas, but in terms of reception category, the spring antenna is still not good. Test results show that the Yagi antenna significantly outperforms the spring antenna, maintaining better signal strength at longer distances due to its effective electromagnetic energy focus.

Manoeuvre Target Tracking in Wireless Sensor Networks Using Convolutional Bi-Directional Long Short-Term Memory Neural Networks and Extended Kalman Filtering.

Aiming at the problem that traditional wireless sensor networks produce errors in the positioning and tracking of motorised targets due to noise interference, this paper proposes a motorised target tracking method with a convolutional bi-directional long and short-term memory neural network and extended Kalman filtering, which is trained by using the simulated RSSI value and the actual target value of motorised targets collected from the convolutional bi-directional neural network to the sensor anchor node, so as to obtain a more accurate initial value of the manoeuvre target, and at the same time, the extended Kalman filtering method is used to accurately locate and track the real-time target, so as to obtain the accurate positioning and tracking information of the real-time target. Through experimental simulation, it can be seen that the algorithm proposed in this paper has good tracking effect in both linear manoeuvre target tracking scenarios and non-linear manoeuvre target tracking scenarios.

Description and analysis of Sigfox received signal strength indicator dataset by using statistical techniques

Low power wide area network (LPWAN) technology has expanded and is essential in the development of applications for the internet of things (IoT). The Sigfox LPWAN network is characterized by its long-range coverage, low cost and power consumption. In this article, a set of 5174 values is analyzed, containing 1606 null RSSI data, obtained with the Sipy module and MicroPython, which provide a coverage map of several points with a resolution of 200 meters deployed in Quito–Ecuador. It is evaluated the type of distribution to which the set of network measurements is adjusted and an optimal 900 MHz propagation model in suburban environments is determined from the measurements obtained from the known base station. As a result, the lost values of RSSI were predicted using the inverse normal distribution method in the original values, observing that they conform to a logistic distribution. The data from the base station were subjected to a data augmentation algorithm designed in MATLAB, determining that the stanford university interim (SUI) model reduces the precision error in the trend of the curve by not presenting changes greater than 5 dB, achieving a precision of 97% with respect to the fit of the curve of the data.

A Survey of Internet of Things based Indoor Positioning Systems based on Bluetooth Low Energy Beacon

The global positioning systems (GPS) and cellular systems face inherent limitations when it comes to enclosed environments like shopping malls, hospitals, warehouses, as they have significant shadowing effects that cause the signals to be distorted. There have been many studies on different technologies and techniques aiming to find the optimum approach to be used for indoor positioning systems (IPS). Among all the technologies adapted by researchers all around the world, Bluetooth Low Energy (BLE) beacons have been a prevalent choice for many, due to its deploying flexibility, low cost, low power consumption and ability to provide very advanced services to users. It is arduous to obtain RSSI values with great accuracy because the signals can be easily intervened by many factors like humidity, temperature, physical barriers, and interference from decoherent signals. In this paper, we presented a comparative analysis of different, fairly recent IPS that are based on BLE beacons by classifying the different proposed approaches in a structured and systematic manner and traversing the issues and challenges that exist with each technique. The accuracy of the results can be enhanced by using the most suitable positioning algorithm, the orientation of the beacon setup, and optimization methods used. A preliminary result from a case study using BLE beacons with K-Nearest Neighbours (KNN) based fingerprinting approach for indoor positioning estimation shows 86.67% accuracy.

A BLE beacon global tracking strategy for small robot using an ESP32 beacon system and GPS

This study aims to estimate the position of a small robot in both outdoor and indoor environments using a combination of RSSI-to-distance calculation, trilateration, and MQTT protocol for communication between ESP32 stations and the server. RSSI is utilized to approximate the distance between the ESP32 and the beacon, while trilateration is employed to determine the precise position of the beacon. The ratio of the imaginary circles is calculated by various signal measurement techniques, and the MQTT protocol is used to set up communication between ESP32 stations and the server. Once the beacon device is visible to all three ESP32 modules, trilateration takes place, and the position of the BLE beacon is displayed as a web page. The server collects the largest RSSI values from the nearest three ESP32 stations, and trilateration is performed from the distances obtained, with the coordinates being sent to the dashboard for visual representation. This strategy is supported by a GPS in outdoor environments, and indoors when structures allow it. Furthermore, the study includes the implementation of an experimental procedure and findings that involve utilizing ESP32 modules as scanning stations to track a BLE beacon.

Performance Evaluation of Collision Avoidance for Multi-node LoRa Networks based on TDMA and CSMA Algorithm

LoRa can be used as the communication technology for the intelligent monitoring system. However, LoRa is usually used for outdoor communication. The usage of LoRa as indoor communication has many challenges. One of the challenges is that collision happens when using standard LoRa devices with only one channel. The algorithms based on TDMA (Time-division Multiple Access) and CSMA (Carrier-sense Multiple Access) protocols can be used to address this challenge. These two algorithms can be modified by applying the device that is the center of the network (gateway) as a central control and the data transmitter (sensor node) as a passive device. The test was conducted on the Intelligent Laboratory Monitoring System to evaluate this design on a multi-node LoRa network. RSSI testing proves that the distance and building interference affect the signal strength or RSSI of sensor nodes, so the average RSSI value is -73.75 with an RSSI threshold of value -106. The gateway successfully collected each sensor node data with an average success of about 64.953%. The experiment results show the success rate of the CSMA-based algorithm is 10% versus 100% in TDMA-based algorithm; the delay is 4125 ms for CSMA-based and 428.3 ms for TDMA-based. This result means that the CSMA-based algorithm is more complex, takes more time to process the data than the TDMA-based algorithm, has a low success rate, and is more prone to collisions.

Analyzing Collaborative Technology Wi-Fi Bluetooth for localization in Indoor Positioning System in indoor premises

For tracking people or object’s Location in the indoor environments, a network device is suggested known as IPS.. This technology mainly used because of supervising the health, position, guidance in different sectors like Universities, museums, airports, hospitals and warehouses the main advantages of IPS with distinct feature like reduction of material and energy cost over time that has huge impact compared to other technology which are more costly. Among various technology like (UWB) Wireless Fidelity (Wi-Fi) Bluetooth Low Energy (BLE). (Wi-Fi)Technology is an outstanding approach for indoor navigation and positioning due to already available Wi-Fi Infrastructure Wireless IPS has categorized into two approaches :geometrical –calculation based and Scene –Analysis based former relies on measurement of geometrical parameter of Distance and angles by physical characteristics of Signal. RSS is the performance parameter used for achieving robustness and accuracy which is most concerned factor for current scenario Most Recent Research has solved the problem of inconsistency on Received Signal Strength (RSS) using fingerprint method. But the RSSI that received may contain some noise. This paper mainly proposed a method to estimate or tracking the real position of dynamic user. With RSSI value as input to be processed and the result of it will be a location (x, y) value, repeat the process to create an estimate coordinate map of route taken. Our proposed method is based on fingerprinting with weighted sum of four nearest reference access point to estimate the position of dynamic user then using Extended Kalman Filter as a tracking algorithm. In this paper we try new ways to collect the data of RSS by dynamically collecting the data in many routes to see whether the proposed algorithm could estimate the position better. We achieve an average mean of error around 2cm using Weighted Sum using Extended Kalman Filter tested on dynamic data. Key words: Indoor Positioning System, Dynamic User Localization, Fingerprinting Method, Weighted Sum Model, Extended Kalman Filter

RSSI Measurement Analysis of Zigbee-Based Wireless Sensor Networks in Various Topologies for Solar Panel Monitoring

Abstract— Solar panels require performance monitoring when energy shortages occur in the area. Monitoring solar panels requires a detection device to detect solar panels, including the ACS712 current sensor for monitoring the output current of the solar panel, a DC voltage sensor for monitoring battery performance, and a DHT11 temperature sensor for monitoring the temperature of the solar panel storage battery. The WSN technology that can work is ZigBee communication. This ZigBee communication research uses various topology methods, including star, tree, and mesh topologies. Solar panel monitoring tests are carried out indoors and outdoors. The ZigBee communication device used is the XBee S2C device, which operates at a frequency of 2.4 GHz. From a comparison of various topologies, the mesh topology is a topology with good performance because it has the characteristic of choosing a router with the fastest path to reach the coordinator. It is proven by monitoring solar panels with an optimal distance of 80 m, which is carried out from outdoors with an RSSI value of -84 dBm, a throughput of 0.55 kbps, and a delay of 2.77 ms, producing power for 150 minutes with an average current of 0.14 A, voltage of 9.86 V, and temperature of 31.48°C. The number of disturbances and weather conditions greatly affect signal propagation, which can hamper the data transmission process. Throughput fluctuates due to uncertain weather conditions, and delay fluctuates due to a lot of interference from other radio signals.
 Keyworrds— Wireless Sensor Nirbael (WSN), RSSI, ZigBee, Panel Surya, Thinger.IO

Oil Filter Machine for Deep Frying with Smartphone Control and Monitoring using Client-Server Communication Protocol

The prevalence of fried snack consumption in our surroundings has become a widespread phenomenon. These fried snacks, commonly relished by many, are frequently served as side dishes with our main meals and are also a popular choice for satisfying quick hunger cravings. By utilizing the client-server communication method, this device can be assisted in its operation. The device employs ESP8266 as both the transmitter and receiver, while a smartphone serves as the control and monitoring tool. The primary purpose of this setup is to enhance the efficiency of oil-based food consumption, promoting healthier habits. The data collected from the device is split into two categories. Firstly, the communication data consists of the average RSSI (-52dBm) measured at a distance of 1 meter, with RSSI values increasing and becoming more susceptible as the distance grows. Secondly, the machine was tested for oil drainage in food, resulting in a weight decrease of 2.6% after 60 seconds of device usage, and the percentage of weight reduction increased with the given time.

LoRa based long-range traceable life jacket system design

It is recorded that around 100 people per year die due to fishing boat accidents, the majority of whom are small fishermen with vessels under 10 GT. LoRa is a license-free power-saving long-distance communication technology that can send data packets of up to 15 km in the ocean. The longrange power can be used to determine the location of fishermen when an accident occurs at sea. This research aims to implement and test the performance of LoRa Ebyte E22-400T30D for sending coordinate data on fishermen’s whereabouts in the form of life jackets. The performance observed is the relationship between the distance and the RSSI value obtained. The tests were performed until the furthest distance was reached. The test was carried out at Pangandaran Beach, and the receiver was placed at an altitude of 129 m toward the beach. The data will be displayed and stored on the Thinger.io website. The test results obtained with the furthest distance achieved were 12.983 km with a battery life of 5.99 hours. The RSSI value obtained tended to worsen with increasing distance. Apart from the distance, it was also found that obstructions in the form of trees could reduce the RSSI value.

Implementation of LoRa on entrance and exit communication as determination of access to AI building, State Polytechnic of Malang

The COVID-19 pandemic has changed many areas of life. One of the consequences is that the learning zone causes reduced mobility and limited face-to-face meetings. State Polytechnic of Malang in overcoming face-to-face learning, especially practical learning in the AI ??Building, of course, many students, not only have the need for practical lectures. The research that the author is doing here is a field research using a quantitative approach. This research was conducted at the AI Building of the State Polytechnic of Malang. In collecting the data needed the author uses observation techniques. Discussion used data analysis methods. The results of the research for the RSSI pattern with the transmit power set at 18dBm lora and the antenna frequency used at 433MHz obtained the RSSI value. At a distance of 2m to 8m there is a decrease in RSSI starting from -57dBm to -80dBm, continuing from a distance of 8m to 42m there is an ups and downs in RSSI. The throughput result is strongly influenced by the value of bytes and the time the throughput value when done twice scanning is smaller than four times scanning because the scanning processes have different times, this is in accordance with the calculation formula.

Implementation of Lora and CoAP Protocol in Hydroponic Plant Water Pump Control

Hydroponics is the cultivation of plants without using soil media, but using water media that contains nutrients and minerals. To observe the growth parameters of hydroponic plants, it is still necessary to come directly to the hydroponic site and provide the nutrients needed manually. In time efficiency, the use of Internet of Things (IoT) is needed so that there is no need to come directly to the hydroponic site. LoRa is a Low Power Wide Area Network (LPWAN) communication system. This research uses sensor nodes, middleware, and client nodes as well as the Constrained Application Protocol (CoAP) protocol for clients to access the value of sensors to control automatic pumps so that nutrients for plants can be given directly without the need to come to the hydroponic site. The result of the implementation is that the water pump control can run properly until the plants can be harvested. The performance testing is done so that LoRa can transmit data at a distance of 1 km with an RSSI value of -114 dBm.

Adaptive elliptic trajectory-based received signal strength indicator antenna tracking algorithm

The continuous telemetry transmission between unmanned aerial vehicles (UAVs) and ground control stations is important particularly in scenarios lacking global positioning system (GPS) data. This paper proposes an adaptive novel elliptic trajectory formula-based tracking algorithm for received signal strength indicator (ANETF-RSSI) which dynamically optimizes model parameters based on energy-associated RSSI measurement errors. ANETF-RSSI generates a variable two-dimensional (2D) RSSI map to identify optimal paths, even under challenging conditions like circular flight paths, varying operating ranges, and accelerated maneuvering, which causes uncertainty into RSSI measurements during flight. In contrast to previous methods, the proposed approach eliminates the reliance on telemetry data such as GPS or complex multiantenna configurations, ensuring robust UAV communication continuity across routes ranging from 100 m to 100 km, even as the UAV rotates around the antenna. This method offers substantial contributions, including enhanced monitoring precision, simplified hardware configurations, continuous tracking with superior accuracy, and adaptability to diverse range routes without the need for preflight parameter tuning. Performance evaluations demonstrate that the proposed ANETF-RSSI method consistently outperforms existing technique, improving nominal performance by 32.02% in the most challenging operational scenarios and achieving a remarkable 48.76% improvement in minimum RSSI values. Consequently, this research provides a versatile and adaptive tracking solution for unexpected UAV flight trajectories.

LoRa and IoT-based Heart Rate and Temperature Monitoring Tool Using MQTT Protocol

Heart rate is one of the most important organs in the human body as it plays a role in the circulatory system. Body temperature is the result of the body's metabolic processes and is influenced by external and internal factors. In this research, we design a monitoring tool that uses LoRa and IoT technology to monitor heart rate and human body temperature. This tool aims to provide real-time health monitoring and can communicate remotely. MQTT allows efficient data transmission between connected devices in the network. Pulse heart rate sensor and temperature sensor MLX90614 The data obtained from these two sensors is sent through the LoRa network to the LoRa gateway. The LoRa gateway functions as a link between the monitoring device and the MQTT server. The gateway receives data from the monitoring device via the LoRa network and forwards it to the MQTT server via an internet connection. The MQTT server sends the data to an application that can be accessed via a smartphone. The test results show that the RSSI value of -72.5 dBm is obtained when the minimum distance is 5 metres. The lowest value for RSSI, which is -93.5 dBm, is obtained at the maximum testing distance of about 55 metres. For the results of the packet loss value is 0% occurs at a closer distance, but at a distance of 50m (5%) and at a distance of 55m (20%) indicates that the signal begins to weaken or experience interference at a greater distance

Wearable Wireless Sensor Network for Mitigating COVID-19 Transmission Through Physical Distancing

The global community is currently facing a critical situation with the widespread transmission of the Covid-19 virus. The rapid increase in Covid-19 cases has necessitated immediate action and treatment. As the World Health Organization (WHO) recommended, maintaining a minimum distance of one meter between individuals is an effective preventive measure to avoid transmission through respiratory droplets. To address this issue, this paper introduces a cost-effective design and implementation of a wearable wireless sensor network using the ESP32 microcontroller and Bluetooth Low-Energy (BLE) technology that promotes physical distancing and contact tracing to mitigate the spread of COVID-19. In this research, we have determined that the safe distance between individuals is 1.5 meters. Proximity testing has indicated that an RSSI value of -62 dBm corresponds to a distance below 1.5 meters. Hence, we set -62 dBm as the distance threshold between wearable devices to ensure safe physical distancing. These wearable wireless sensor network devices are intended to assist individuals in maintaining a safe distance from others, thereby reducing the risk of COVID-19 transmission.

ANALYSIS THE IMPACT OF ENCLOSING VARIOUS MATERIALS ON THE STRENGTH OF WIFI SIGNAL RECEPTION

Installation Wi-Fi is sometimes hindered by obstacles such as wood, concrete, and glass. The presence of these materials may affect the signal strength received by the user. Therefore, research was carried out by enclosing router using PVC, acrylic and glass materials with a thickness of 2mm, 3mm and 5mm and a distance of 2m, 4m, 6m, 8m, 10m, 12m, 10.2m and 11.4m for RSSI measurements and Quality of Service at a distance of 12m and 11.4m in the morning, afternoon and evening. The measurement results show a decrease in RSSI depending on the obstacle and distance. This is because the signal experiences diffraction and reflection which causes the signal strength to weaken and the farther the distance the weaker the signal. Measurements at the moment non-line of sight has quite poor results, especially when the glass barrier with a thickness of 5mm is at a distance of 11.4 with an average RSSI value of 74.6 dBm. QoS parameter results show Throughput When video streaming all have a bad category due to low number of packets. Parameter Packet Loss all of them are in a very good category, showing the least missing packets. Parameter Latency all of them have a very good category though Throughput low, influenced by the number of incoming packets. Parameter Jitter good with 2mm and 3mm barriers, while 5mm in the afternoon is moderate, influenced by Latency.

OPTIMIZATION OF ENERGY CONSUMPTION IN SENSOR NODE BASED ON RECEIVED SIGNAL STRENGTH INDICATOR (RSSI) AND SLEEP AWAKE METHOD

The transmission power management in Wireless Sensor Networks (WSN) is a critical problem. This research investigated optimizing power consumption based on transmission power (Tx Power) level according to RSSI and periodic transmission time. We investigated the RSSI value by varying Tx Power Level to get the optimum Tx Power Level. We found the optimum periodic transmission time by transmitting the data with various transmission times. By varying the Tx Power Level, we found the optimum Tx Power Level, resulting in the power consumption decreasing by about 42% and the power supply’s lifetime increasing by about 71% in the 280 m distance between the sensor node and gateway, with a 108 Wh power supply. By varying the periodic transmission time, we found that the optimum periodic transmission time is 8 seconds. Combining the optimum Tx Power Level and periodic transmission time, we found that the power supply’s lifetime is 40 times longer. This result is helpful for WSN applications in remote areas.

LoRa-Based Low-Cost Nanosatellite for Emerging Communication Networks in Complex Scenarios

Wireless broadband coverage has reached 95% worldwide. However, its trend is expected to stay the same in the following years, presenting challenges for scenarios such as remote villages and their surrounding environments. Inaccessibility to these areas for installing terrestrial base stations is the main challenge to bridge the connectivity gap. In addition, there are emergencies, for instance, earthquakes or war areas, that require a fast communication reaction by developing networks that are less susceptible to disruption. Therefore, we propose a low-cost, green-based nanosatellite system to provide complete coverage in hard-to-reach areas using long-range communication. The system comprises a pilot station, a base station, and a CubeSat with sensor data collector capabilities acting as a repeater. Our system can be built within hours with a 3D printer using common material, providing a flexible environment where components can be replaced freely according to user requirements, such as sensors and communication protocols. The experiments are performed in Spain by two test sets validating the communication among all components, with RSSI values below −148 dBm and the longest distance above 14 km. We highlight the reduction in the environmental impact of this proposal using a balloon-based launch platform that contributes to sustainable development.

LoRaWAN: Solution for Monitoring Differential Pressure Room in Pharmaceutical Industry

The air conditioning system is a process continuous air control of air temperature, air humidity, air cleanliness, air quality, speed indoor air, air distribution evenly throughout the room as well control the noise that can caused by the air conditioning equipment itself according to the needs and conditions wanted especially in drug factories. In This research we use IoT Technologi to provide system to monitoring Differential Pressure room in Pharmaceutical room based on LoRaWAN. LoRaWAN is one of the LPWAN technologies which also provides a wide range of coverage, low power, and low cost in the implementation. The result of this study are very satisfactory, it can be seen that the results of the LoRaWAN implementation are very good with an indication of the worst RSSI value of -91 dbm and an error value on the Differential Pressure sensor device of 0.65 Pascal.

Artificial Neural Network for Indoor Localization Based on Progressive Subdivided Quadrant Method

The exterior location of a user can be accurately determined using a global positioning system (GPS). However, accurately locating objects indoors poses challenges due to signal penetration limitations within buildings. In this study, an MLP with stochastic gradient descent (SGD) among artificial neural networks (ANNs) and signal strength indicator (RSSI) data received from a Zigbee sensor are used to estimate the indoor location of an object. Four fixed nodes (FNs) were placed at the corners of an unobstructed area measuring 3 m in both length and width. Within this designated space, mobile nodes (MNs) captured position data and received RSSI values from the nodes to establish a comprehensive database. To enhance the precision of our results, we used a data augmentation approach which effectively expanded the pool of selected cells. We also divided the area into sectors using an ANN to increase the estimation accuracy, focusing on selecting sectors that had measurements. To enhance both accuracy and computational speed in selecting coordinates, we used B-spline surface equations. This method, which is similar to using a lookup table, brought noticeable benefits: for indoor locations, the error margin decreased below the threshold of sensor hardware tolerance as the number of segmentation steps increased. By comparing our proposed deep learning methodology with the traditional fingerprinting technique that utilizes a progressive segmentation algorithm, we verified the accuracy and cost-effectiveness of our method. It is expected that this research will facilitate the development of practical indoor location-based services that can estimate accurate indoor locations with minimal data.