This document presents basic theory about how to setup a network solution fortransferring sensor data and also gives instructions on how to set up some of itsbuilding blocks. This document mainly handles LoRa, LoRaWAN, Chirpstack,Arduino and some other related frameworks. / Denna anvisning går igenom grundläggande teorier om hur man sätter upp ennätverkslösning för att kommunicera sensor data och ger även instruktioner förhur man sätter upp några av dessa enheter. Det här dokumentet handlar omLoRa, LoRAWAN, Chirpstack, Arduino och några andra relaterade ramverk. / <p>Högskoleingengör och/eller Teknisk Kanidat examen 16hp.</p>

IoT stands for the Internet of Things and is a concept that has been around since 1999. IoT are objects around us that collects data and connects to controls or other machines via the internet and is a field that constantly growing every year. The most used communication for IoT devices is wireless communication. The term is broad and contains many different protocols, e.g. Bluetooth, WiFi, and LoRa. LoRa, which is short for Long Range is an energy-efficient long-range wireless data transfer technology that sends small data packets between IoT nodes and LoRa receivers. A LoRa receiver can communicate with hundreds of nodes and the product has spread widely throughout the world. LoRa is the term for the physical layer for communication and LoRaWAN corresponds to the communication protocol. Simulating a LoRaWAN network is interesting as it provides an opportunity to get an idea of how it might work. This can result in increased use of network simulations in experiments and give the opportunity for companies, as well as private individuals to take the first step towards using LoRa and benefit from the results. Ns-3 is a network simulator and has been selected for use in this work. The use of a network simulator always raises questions about how credible the simulation portraits reality. With a collaboration with Etteplan, the issue for the work was formulated to: ● How well can simulation of LoRaWAN correspond to physical measurement when used between a LoRa receiver and IoT node in a free-vision environment? To answer the question, a simulation of a LoRaWAN network in the simulator Ns-3 was tested and then compared with results based on reality. The factor that was compared in the simulation against reality is the signal strength and how it is affected by spreading factors, different bandwidths and distances. The spreading factors 7 to 11 and the bandwidth 125, 250 and 500 kHz have been used at the distances 211, 1800 and 3500 meters. After analysing the data collected during the experiment it can be seen that the signal strength became stronger the higher the bandwidth used in the reality, however similar tests resulted in the simulation to the contrary. The higher bandwidth contributed to a lower signal strength. The spreading factor behaved differently in the simulation compared to the reality because it had a bigger impact on the signal strength. The conclusion of this can be that the simulation was able to integrate the signal for a longer time with higher spreading factor and this led to better signal strength as it reduced the interference of communication. However, one can conclude that the simulation showed a good picture of what a real scenario might look like between a LoRa receiver and IoT node.

Im Energie- und Produktionssektor ist für das Heben von Potentialen für Energie- und Ressourceneffizienz von Prozessen viel Sensorik notwendig. Verkabelte Systeme sind dafür aufgrund hoher Installationskosten und geringer Flexibilität oftmals nicht geeignet. Notwendig ist ein kostengünstiges, nachrüstbares und energieautarkes drahtloses Sensornetzwerk (WSN – Wireless Sensor Network) für Energie- und Condition Monitoring (Strom-, Spannungs-, Vibrations-, Temperaturmessung). Ein wesentlicher Innovationsschritt ist die Anwendung und intelligente Kombination neuer Funktechnologien wie UWB (Ultra-Wideband) und LoRa (Long Range) sowie von Energy Harvesting zum autarken Betrieb der Sensorknoten. Mit einem systemischen Ansatz der Kombination vorgenannter Komponenten wird das Sensornetz hinsichtlich Verlässlichkeit, Skalierbarkeit und Flexibilität in Bezug auf die Anwendung optimiert. Der Proof-of-Concept (PoC) wird mit einem Testaufbau des WSN im Labormaßstab an konkreten Use Cases aus den Bereichen Windkraftanlagen und industrieller Produktion erbracht.

The Internet was initially built around networks based on physical cables, the next step to improve the accessibility of the Internet came with the introduction of wireless communication. the next step to improving accessibility to the Internet came with the introduction of wireless communication. Because the IoT products are wirelessly connected, they need an internal power source in the form of a battery. Many of the existing communication protocols are therefore not suitable for IoT solutions because they are power consuming. Alternatives to these communication protocols have therefore been developed, for example LTE-M, NB-IoT and LoRaWAN. The study was conducted in cooperation with Etteplan. Etteplan want to invest in LoRaWAN and thus want to gain deeper knowledge within LoRaWAN. Thus, it was chosen to investigate how different factors affect the signal strength transmission time in a LoRaWAN. The focus of the study has thus been on the communication between an IoT node and a receiver in a LoRaWAN, thus the purpose of the study: To show how different data rates, distances and environments affect the quality of information sent from an IoT node to a receiver in LoRaWAN. Design science research was used as a research method, in design science research an artefact is constructed and then studied. In this study, a LoRaWAN was constructed and the communication between an IoT node and receiver in this LoRaWAN was studied. To study the communication between the IoT node and the receiver, two experiments were performed. The experiments were performed simultaneously where the difference was in the data collected, one experiment collected the signal strength and the second the transmission time. The experiment was conducted in two different environments, one with a clear view and one with blockages. In the experiment, the IoT node was positioned at different distances with different data rates. The result of the study shows how different data rates, distances and environments affected the quality of information between an IoT node and receiver and how they relate to previous research. Data rate was the factor that affected the quality of the information most. Data rate had minimal impact on signal strength, but great impact on number of lost data packet and transmission times. The two different environments had no effect on the transmission time, but the signal strength was over 10 dbm lower in the urban environment than with clear view. The distance had no effect on transmission time and minimal impact on signal strength. / Internet var i begynnelsen uppbyggt kring nätverk baserade på fysiska kablar, nästa steg för att förbättra tillgängligheten till Internet kom med introduktionen av trådlös kommunikation. Ett nytt begrepp dök upp vid millennieskiftet, Internet of Things (IoT). Tanken bakom IoT är att olika typer av produkter, som exempelvis tandborstar och kylskåp trådlöst kopplas upp mot Internet. Eftersom IoT-produkterna är trådlöst uppkopplade behöver de en intern strömkälla i form av ett batteri. Många av de existerande kommunikationsprotokollen lämpar sig därför inte för IoT-lösningar eftersom dessa är strömkrävande. Alternativ till dessa kommunikationsprotokoll har därför tagits fram, till exempel LTE-M, NB-IoT och LoRaWAN. Studien utfördes i samarbete med Etteplan. Etteplan vill satsa på LoRaWAN och vill därmed få en djupare kunskap inom LoRaWAN. Därmed valdes det att undersöka hur olika faktorer påverkar signalstyrkan och sändningstiden i ett LoRaWAN. Studiens fokus har därmed varit på kommunikationen mellan en IoT-nod och en mottagare i ett LoRaWAN, därmed är studiens syfte: Att visa på hur olika datahastigheter, avstånd och miljöer påverkar kvaliteten på informationen som sänds från en IoT-nod till en mottagare i ett LoRaWAN. Design science research användes som forskningsmetod då i design science research konstrueras en artefakt som att sedan undersöks. I studiens fall konstruerades ett LoRaWAN där sedan kommunikationen mellan en IoT-nod och mottagare i detta LoRaWAN studerades. För att studera kommunikationen mellan en IoT-nod och en mottagare utfördes två experiment. Experimenten utfördes samtidigt där skillnaden låg i datat som samlades in, det ena experimentet samlade in signalstyrkan och den andra sändningstiden. Experimentet utfördes i två olika miljöer, en med fri sikt och en med blockeringar. I experimentet positionerades IoT-noden på olika avstånd med olika datahastigheter. Resultatet från studien visar hur olika datahastigheter, avstånd och miljöer påverkade kvaliteten på informationen mellan en IoT-nod och mottagare och hur de relateras till tidigare forskning. Datahastigheten var den faktorn som påverkade kvaliteten på informationen mest. Datahastigheten hade minimal påverkan på signalstyrkan, men stor påverkan på antal förlorade datapaket och sändningstider. De två olika miljöerna hade ingen påverkan på sändningstiden, men signalstyrkan var över 10 dbm lägre i stadsmiljön än med fri sikt. Avståndet hade ingen påverkan på sändningstiden och minimal påverkan på signalstyrkan.

Syftet med det här arbetet är att undersöka hur överföringstid skiljer sig i förhållande tillskalbarhet mellan två back-endlösningar i LoRaWAN. Lösningarna är Node-RED ochChirpstack. Studien genomförs med hjälp av metoderna experiment och fallstudie. Iexperimentet utfördes ett t-test för att svara på om nollhypotesen kan förkastas eller inte.Resultatet visar att nollhypotesen inte kunde förkastas, och att det inte är någon skillnadi skalbarhet. Bortsett från t-testet visar resultaten att Chirpstack skalar sämre änNode-RED vid fyra eller fler tillagda enheter. Slutsatsen är däremot att skillnaden ärtillräckligt liten för att bedömas obetydlig för val av back-endlösning. Studien ärbegränsad till sju uppkopplade LoRa-enheter. / The purpose of this study is to investigate how transfer time differs in relation toscalability between two back-end solutions in LoRaWAN. The solutions are Node-REDand Chirpstack. The study is carried out using the methods experiment and case study.In the experiment, a t-test was performed to answer whether the null hypothesis can berejected or not. The results show that the null hypothesis could not be rejected, and thatthere is no difference in scalability. Apart from the t-test, the results show that Chirpstackscales worse than Node-RED at four or more added LoRa-units. The conclusion,however, is that the difference is small enough to be considered insignificant for thechoice of back-end solution. The study is limited to seven connected LoRa units.

Internet of Things (IoT) är ett koncept som fått mycket uppmärksamhet från forskare och utövare av IoT världen över. IoT kan beskrivas som ett nätverk där vardagliga föremål kommunicerar med varandra eller med människor. IoT kommer att bygga ut internet genom att integrera föremål för kommunicering via inbäddade system, detta leder till ett distribuerat nätverk av enheter som kommunicerar med människor och andra IoT-enheter. Härnösand Miljö &amp; Energi AB (HEMAB), är en av ägarna till ServaNet och är ett företag som vill utöka sitt testområde för IoT-sensorer som använder LoRa-teknik för att kommunicera. HEMAB är en av ägarna till ServaNet. Studien har konstruerat metoder för mätning av höjdskillnad från data av en barometer och en accelerometer. Resultatet jämför de två sensorerna med avseende på hur tillförlitligt de kan mäta höjdskillnad över tid. Accelerometern ger mer tillförlitliga resultat som ligger närmare verkligheten, på lägre höjder, med en kortare mätperiod i jämförelse med barometern. Däremot, visar barometern mer tillförlitliga värden på högre höjder, och mer tillförlitligt värde än accelerometern på den högsta testade höjden. Anledningen till att accelerometern ger mindre tillförlitliga resultat på högre höjder med längre mätperiod, beror på det sättet dubbelintegrering tar med sig felande och avstickande värden som blir större och större ju längre tid som integreras. Barometern ger osäkra värden på lägre höjd på grund av att sensorn ger spridda värden redan då den ligger stillastående, detta jämnas ut på högre höjder. LoRaWAN är en lämplig teknik för att kommunicera våghöjd, förutsatt att beräkningar görs på prototypen och endast våghöjden skickas över LoRa, inte sensordata. / Internet of Things (IoT), is a concept that has received a lot of attention from researchers and practitioners of IoT worldwide. IoT can be described as a network where everyday objects communicate with each other or with people. IoT will expand the internet by integrating objects for communication via embedded systems, this leads to a distributed network of devices that communicate with people and other IoT devices. Härnösand Miljö &amp; Energi AB (HEMAB), is one of the owners of ServaNet and is a company that wants to expand its test area for IoT sensors that use LoRa-technology to communicate. HEMAB is one of the owners of ServaNet, as ServaNet is the city network in Härnösand. This study has constructed a method for each sensor that can measure height difference. The result compares a barometer and an accelerometer with respect to how reliably they can measure height difference over time. The accelerometer gives more reliable results that are closer to the reality, at lower altitudes, with a shorter measurement period compared to the barometer. On the other hand, the barometer shows more reliable measurements at higher altitudes, and more accurate measurement than the accelerometer at the highest tested altitude. The reason why the accelerometer performs worse at higher altitudes with longer measurement periods, is due to the way double integration stacks up errors that grows with time, resulting in larger errors for longer periods of measurements. The barometer gives no reliable measurements at lower altitudes, due to the sensor giving scattered values even when the sensor is stationary, this evens out at higher altitudes. LoRaWAN is a suitable technology for communicating wave height, provided that calculations are made on the prototype and only the wave height is sent over LoRa, not sensor-data.  The outcome of the benchmarks measurement showed that increasing the number of nodes would not result in superior performance. It was noted that an optimal number of nodes was found to be between 1 and 20 for all the tests performed. The study showed that no load balancer could be considered a clear winner, instead, different configurations of load balancers performed varyingly well at different tests.

Memoria para optar al título de Ingeniero Civil Eléctrico / El paradigma de comunicación Internet of Things (IoT), el cual plantea la posibilidad de interconectar objetos cotidianos y toda clase de dispositivos convencionales a Internet, está actualmente en pleno desarrollo. El gran número de nodos que se espera conectar a Internet exige a su vez la implementación a gran escala de Internet Protocol versión 6 (IPv6). IoT busca el desarrollo de nuevas aplicaciones y ha impulsado la creación de nuevas arquitecturas de red y nuevas clases de dispositivos. Las redes Low Power Wide Area Networks (LPWAN) han surgido recientemente como una evolución natural del concepto Wireless Sensor Networks (WSN), redes de sensores in- terconectadas. A la luz del IoT, las nuevas redes LPWAN abren un nuevo campo de desarrollo, principalmente enfocado en servicios de monitoreo y afines que se desarrollen en áreas am- plias y no requieran grandes tasas de transferencia. Los dispositivos LPWAN se caracterizan por ser de bajo consumo energético y de bajo costo, facilitando su despliegue masivo por largos períodos sin necesidad de recargar sus baterías. Long Range Wide Area Network (LoRaWAN) es una de las primeras y principales tec- nologías LPWAN, y presenta una gran flexibilidad que la hace ideal para redes de diseño propio. En América funciona en la banda industrial, científica y médica (ISM) alrededor de los 915 MHz. Sin embargo, también existen muchas otras tecnologías LPWAN con arquitec- turas y protocolos propietarios, lo que dificulta alcanzar la interoperabilidad que se desea en el entorno IoT. El grupo de trabajo para la implementación de IPv6 sobre redes LPWAN (lpwan WG) perteneciente al Internet Engineering Task Force (IETF) se encuentra actualmente desarrol- lando un mecanismo de compresión y fragmentación de paquetes IPv6 para redes LPWAN denominado Static Context Header Compression (SCHC). El esquema de compresión se en- cuentra terminado, pero aún no ha sido implementado ni evaluado de manera oficial. En este trabajo se presenta una plataforma experimental para la implementación y eval- uación del mecanismo SCHC sobre una red LoRaWAN consistente en un nodo terminal Mi- crochip y un Radio Gateway (RG) de Everynet. En su desarrollo se han integrado múltiples y diversas herramientas del campo de las Telecomunicaciones y las Tecnologías de Información y Comunicación (ICT). La plataforma creada logra una implementación básica pero exitosa del esquema de com- presión de SCHC. Por medio de ella se ha llevado a cabo una evaluación preliminar del funcionamiento de SCHC, analizando el nivel de compresión logrado por el mecanismo para tres contextos de comunicación característicos de una red LPWAN. Los resultados obtenidos son positivos.

This work deal with analysis of LoRa wireless communication protocol and LoRaWAN MAC layer. Analysis aims to LoRa packet detection using software defined radio, wireless trafic and information which can be extracted (sniffed) from wireless communication between devices which uses LoRaWAN MAC layer. Next part of this work describes two wireless devices development. First one for demonstration purporses with some type of commercial LoRa modules and second to paralell sniffing of LoRa wireless communication on various frequency channels.

This Master thesis is focused on the design and consequential realization of the Multi-RAT communication device. The theoretical part describes a comparison of two promising communication LPWA (Low Power Wide Area) technologies that are available to use in the Czech Republic. These technologies are NB-IoT (NarrowBand-Internet of Things) and LoRaWAN (Long Range Wide Area Network). The practical part contains a description used components, their consequential fitting and testing of designed printed circuit board of the device. The thesis also describes the implementation of software and realized measurement. Technical documentation of a device can be found in the appendix of this thesis.

With technology advancements and the prices of electronic components reducing over the last fifteen years, many devices and systems that would have been proprietary only for large companies or industry giants are becoming an everyday household item. Various areas of technology have been benefiting from this but one of the biggest is the Internet of Things (IoT).With the prevalence of IoT, it has been integrated into houses, small businesses, farms, agriculture, building automation, etc. and the user population is now a resource to the industry as they complete personal projects. Within any project there are always limitations, this might be a limited time, limited funds, limited distance, or limitations of the devices being used. This study proposes to evaluate two low-powered networks, Narrowband Internet of Things (NB-IoT)and Long-Range Wide-Area Network(LoRaWAN), in different environments with the goal of understanding where the signal propagation is better and what distances can be reached despite obstructions. Distances and signal propagations, when measured by the manufacturers are often evaluated in ideal conditions which is rarely the case when utilized in the field. This creates a gap in the deployment and the end-users are frequently faced with diminished performances. As IoT is predominantly employed in urban and rural areas this study will focus on those two settings by testing the Received Signal Strength Indicator (RSSI)at various distances. The evaluation testing of the two systems showed each system performing more consistently in rural areas but neither had 100% coverage at any locations.