How Meshify Built an Insurance-focused IoT Solution on AWS
AWS Architecture BlogHow Meshify Built an Insurance-focused IoT Solution on AWSby Grant Fisher, Gordon Hui, and Sid Singh | on03 JAN 2022| inAmazon Elastic Kubernetes Service,Amazon Managed Streaming for Apache Kafka (Amazon MSK),Amazon RDS,Architecture,AWS IoT Core,Intermediate (200)|Permalink|ShareThe ability to analyze your Internet of Things (IoT) data can help you prevent loss, improve safety, boost productivity, and even develop an entirely new business model. This data is even more valuable, with the ever-increasing number of connected devices. Companies useAmazon Web Services (AWS)IoT services to build innovative solutions, including secure edge device connectivity, ingestion, storage, and IoT data analytics.This post describes Meshify’s IoT sensor solution, built on AWS, that helps businesses and organizations prevent property damage and avoid loss for the property-casualty insurance industry. The solution uses real-time data insights, which result in fewer claims, better customer experience, and innovative new insurance products.Through low-power, long-range IoT sensors, and dedicated applications, Meshify can notify customers of potential problems like rapid temperature decreases that could result in freeze damage, or rising humidity levels that could lead to mold. These risks can then be averted, instead of leading to costly damage that can impact small businesses and the insurer’s bottom line.Architecture building blocksThe three building blocks of this technical architecture are the edge portfolio, data ingestion, and data processing and analytics, shown in Figure 1.Figure 1. Building blocks of Meshify’s technical architectureI. Edge portfolio (EP)Starting with the edge sensors, the Meshify edge portfolio covers two types of sensors:LoRaWAN (Low power, long range WAN) sensor suite.This sensor provides the long connectivity range (> 1000 feet) and extended battery life (~ 5 years) needed for enterprise environments.Cellular-based sensors.This sensor is a narrow band/LTE-M device that operates at LTE-M band 2/4/12 radio frequency and uses edge intelligence to conserve battery life.II. Data ingestion (DI)For the LoRaWAN solution, aggregated sensor data at the Meshify gateway is sent to AWS using AWS IoT Core and Meshify’s REST service endpoints.AWS IoT Coreis a managed cloud platform that lets IoT devices easily and securely connect using multiple protocols like HTTP, MQTT, and WebSockets. It expands its protocol coverage through a new fully managed feature calledAWS IoT Core for LoRaWAN. This gives Meshify the ability to connect LoRaWAN wireless devices with the AWS Cloud. AWS IoT Core for LoRaWAN delivers a LoRaWAN network server (LNS) that provides gateway management using the Configuration and Update Server (CUPS) and Firmware Updates Over-The-Air (FUOTA) capabilities.III. Data processing and analytics (DPA)Initial processing of the data is done at the ingestion layer, using Meshify REST API endpoints and the Rules Engine of AWS IoT Core. Meshify applies filtering logic to route relevant events toAmazon Managed Streaming for Apache Kafka (Amazon MSK). Amazon MSK is an AWS streaming data service that manages Apache Kafka infrastructure and operations, streamlining the process of running Apache Kafka applications on AWS.Meshify’s applications then consume the events from Amazon MSK per the configured topic subscription. They enrich and correlate the events with the records with a managed service,Amazon Relational Database Service (RDS). These applications run as scalable containers on another managed service,Amazon Elastic Kubernetes Service (EKS), which runs container applications.Bringing it all together – technical workflowIn Figure 2, we illustrate the technical workflow from the ingestion of field events to their processing, enrichment, and persistence. Finally, we use these events to power risk avoidance decision-making.Figure 2. Technical workflow for Meshify IoT architectureAfter installation, Meshify-designed LoRa sensors transmit information to the cloud through Meshify’s gateways. LoRaWAN capabilities create connectivity between the sensors and the gateways. They establish a low power, wide area network protocol that securely transmits data over a long distance, through walls and floors of even the largest buildings.The Meshify Gateway is a redundant edge system, capable of sending sensor data from various sensors to the Meshify cloud environment. Once the LoRa sensor information is received by the Meshify Gateway, it converts the incoming radio frequency (RF) signals, which support faster transfer rate to Meshify’s cloud environment.Data from the Meshify Gateway and sensors is initially processed at Meshify’s AWS IoT Core and REST service endpoints. These destinations for IoT streaming data help with the initial intake and introduce field data to the Meshify cloud environment. The initial ingestion points can scale automatically based upon the volume of sensor data received. This enables rapid scaling and ease of implementation.After the data has entered the Meshify cloud environment, Meshify uses Amazon EKS and Amazon MSK to process the incoming data stream. Amazon MSK producer and consumer applications within the EKS systems enrich the data streams for the end users and systems to consume.Producer applications running on EKS send processed events to the Amazon MSK service. These events include storing and retrieval of raw data, enriched data, and system-level data.Consumer applications hosted on the EKS pods receive events per the subscribed Amazon MSK topic. Web, mobile, and analytic applications enrich and use these data streams to display data to end users, business teams, and systems operations.Processed events are persisted in Amazon RDS. The databases are used for reporting, machine learning, and other analytics and processing services.Building a scalable IoT solutionMeshify first began work on the Meshify sensors and hosted platform in 2012. In the ensuing decade, Meshify has successfully created a platform to auto-scale upon demand with steady, predictable performance. This gave Meshify both the ability to use only the resources needed, and still have the capacity to handle unexpected voluminous data.As the platform scaled, so did the volume of sensor data, operations and diagnostics data, and metadata from installations and deployments. Building an end-to-end data pipeline that integrates these different data sources and delivers co-related insights at low latency was time well spent.ConclusionIn this post, we’ve shown how Meshify is using AWS services to power their suite of IoT sensors, software, and data platforms. Meshify’s most important architectural enhancements have involved the introduction of managed services, notably AWS IoT Core for LoRaWAN andAmazon MSK. These improvements have primarily focused on the data ingestion, data processing, and analytics stages.Meshify continues to power the data revolution at the intersection of IoT and insurance at the edge, using AWS. Looking ahead, Meshify and HSB are excited at the prospect of scaling the relationship with AWS from cloud computing to the world of edge devices.Learn more about howemerging startups and large enterprises are using AWS IoT servicesto build differentiated products.Meshifyis an IoT technology company and subsidiary ofHSB, based in Austin, TX. Meshify builds pioneering sensor hardware, software, and data analytics solutions that protect businesses from property and equipment damage.Grant FisherGrant Fisher is the Director of Software Engineering for Meshify, HSB’s IoT subsidiary. He is responsible for overseeing the software and systems implementations at Meshify - bringing secure, robust and efficient applications to the customer.Gordon HuiGordon Hui serves as Head of Product for HSB's IoT solution, which is powered by Meshify's IoT technology and data analytics products. In his role, Gordon leads Commercial IoT product vision and strategy, oversees the product roadmap, and directs partner ecosystem activities.Sid SinghSid is a Solutions Architect with Amazon Web Services. He works with the global financial services customers and has more than 10 years of industry experience covering a wide range of technologies. Outside of work, he loves traveling, is an avid foodie, and also a Bavarian beer enthusiast.
The ability to analyze your Internet of Things (IoT) data can help you prevent loss, improve safety, boost productivity, and even develop an entirely new business model. This data is even more valuable, with the ever-increasing number of connected devices. Companies use Amazon Web Services (AWS) IoT services to build innovative solutions, including secure edge […]
Grant Fisher
Amazon Elastic Kubernetes Service Amazon Managed Streaming for Apache Kafka (Amazon MSK) Amazon RDS Architecture AWS IoT Core Intermediate (200)