Measuring Environmental Effects on LoRa Radios in Cold Weather using 915 MHz

The “Internet of Things” (IoT) is a commonplace term in today’s society. Measuring our homes, cities, and farm land, IoT devices and sensor networks help give insight with new amounts and types of data collected. With several billion devices projected to be in use by 2020, an inexpensive, reliable solution for communication is needed. Typically, this would mean Wi-Fi, and in the home that works; but what if the devices are several miles away? LoRaWAN has sought to fll this need, however, appears unreliable given changes in atmospheric conditions. Experiments in Europe have shown a complete communication breakdown when temperatures reach 60◦C, below the 80◦ hardware specifcation. The researcher’s own observations and preliminary test also show inconsistencies in terms of range and received signal strength. This thesis describes the process of designing a physical server-client architecture using a Dragino LoRa client and Raspberry Pis. Using hobbyist-available materials, three LoRa nodes were created to test the effects of cold weather, along with rain and snow. The nodes were deployed from January to the beginning of March, recording communications, weather data, and the received signal strength of packets. This data was then analyzed for factors that affected communication most. The experiment was split into two phases, one for recording the natural environmental conditions, the other, for measuring environmental conditions when heat is applied directly to the LoRa radio chip. Visual representation and statistical correlations were used to determine the relationship between temperature and humidity inside and outside a node, the intensity of rain and snow, and the temperature of the radio chip, compared to the received signal strength (RSS) and received packet ratio (RPR). From the comparisons made, humidity appears to be a leading predictor in LoRa communication reliability. This is followed by temperature, then the amount of rain, and fnally snow. The temperature of the radio chip, from ambient to 60◦C does not seem to affect signal strength or communication in a noticeably impactful way. This shows an indication that communication failure is caused by problems with the antenna or the micro-controller, a distinction other experiments have not made, however the exact distinction between antenna and micro-controller was outside the scope of this study

Scans Framework: Simulation of CUAS Networks and Sensors

Counter Unmanned Aerial System (CUAS) security systems have unrealistic performance expectations hyped on marketing and idealistic testing environments. By developing an agent-based model to simulate these systems, an average performance metric can be obtained, thereby providing better representative values of true system performance. Due to high cost, excessive risk, and exponentially large parameter possibilities, it is unrealistic to test a CUAS system for optimal performance in the real world. Agent-based simulation can provide the necessary variability at a low cost point and allow for numerous parametric possibilities to provide actionable output from the CUAS system. This study describes and documents the Simulation of CUAS Networks and Sensors (SCANS) Framework in a novel attempt at developing a flexible modeling framework for CUAS systems based on device parameters. The core of the framework rests on sensor and communication device agents. These sensors, including Acoustic, Radar, Passive Radio Frequency (RF), and Camera, use input parameters, sensor specifications, and UAS specifications to calculate such values as the sound pressure level, received signal strength, and maximum viewable distance. The communication devices employ a nearest-neighbor routing protocol to pass messages from the system which are then logged by a command and control agent. This framework allows for the flexibility of modeling nearly any CUAS system and is designed to be easily adjusted. The framework is capable of reporting true positives, true negatives, and false negatives in terms of UAS detection. For testing purposes, the SCANS Framework was deployed in AnyLogic and models were developed based on existing, published, empirical studies of sensors and detection UAS

Measuring Environmental Effects on Lora Radios in Cold Weather Using 915 MHz

The “Internet of Things” (IoT) is a commonplace term in today’s society. Measuring our homes, cities, and farm land, IoT devices and sensor networks help give insight with new amounts and types of data collected. With several billion devices projected to be in use by 2020, an inexpensive, reliable solution for communication is needed. Typically, this would mean Wi-Fi, and in the home that works; but what if the devices are several miles away? LoRaWAN has sought to fill this need, however, appears unreliable given changes in atmospheric conditions. Experiments in Europe have shown a complete communication breakdown when temperatures reach 60°C, below the 80° hardware specification. The researcher’s own observations and preliminary test also show inconsistencies in terms of range and received signal strength. This thesis describes the process of designing a physical server-client architecture using a Dragino LoRa client and Raspberry Pis. Using hobbyist-available materials, three LoRa nodes were created to test the effects of cold weather, along with rain and snow. The nodes were deployed from January to the beginning of March, recording communications, weather data, and the received signal strength of packets. This data was then analyzed for factors that affected communication most. The experiment was split into two phases, one for recording the natural environmental conditions, the other, for measuring environmental conditions when heat is applied directly to the LoRa radio chip. Visual representation and statistical correlations were used to determine the relationship between temperature and humidity inside and outside a node, the intensity of rain and snow, and the temperature of the radio chip, compared to the received signal strength (RSS) and received packet ratio (RPR). From the comparisons made, humidity appears to be a leading predictor in LoRa communication reliability. This is followed by temperature, then the amount of rain, and finally snow. The temperature of the radio chip, from ambient to 60°C does not seem to affect signal strength or communication in a noticeably impactful way. This shows an indication that communication failure is caused by problems with the antenna or the micro-controller, a distinction other experiments have not made, however the exact distinction between antenna and micro-controller was outside the scope of this study