IBM Hackathon Produces Innovative Sustainability Solutions on AWS
AWS Architecture BlogIBM Hackathon Produces Innovative Sustainability Solutions on AWSby Dhana Vadivelan, Markus Graulich, and Vlad Zamfirescu | on10 NOV 2021| inArchitecture,AWS Partner Network,Customer Solutions,Sustainability|Permalink|ShareThis post was co-authored by Dhana Vadivelan, Senior Manager, Solutions Architecture, AWS; Markus Graulich, Chief Architect AI EMEA, IBM Consulting; and Vlad Zamfirescu, Senior Solutions Architect, IBM ConsultingOur consulting partner,IBM, organized the “Sustainability Applied 2021” hackathon in September 2021. This three-day event aimed to generate new ideas, create reference architecture patterns using AWS Cloud services, and produce sustainable solutions.This post highlights four reference architectures that were developed during the hackathon. These architectures show you how IBM hack teams used AWS services to resolve real-world sustainability challenges. We hope these architectures inspire you to help address other sustainability challenges with your own solutions.IBM sustainability hackathonAny sustainability research requires acquiring and analyzing large sustainability datasets, such as weather, climate, water, agriculture, and satellite imagery. This requires large storage capacity and often takes a considerable amount of time to complete.TheAmazon Sustainability Data Initiative (ASDI)provides innovators and researchers with sustainability datasets and tools to develop solutions. These datasets are publicly available to anyone on theRegistry of Open Data on AWS.In the hackathon, IBM hack teams used these sample datasets and open APIs fromThe Weather Company(an IBM business) to develop solutions for sustainability challenges.Architecture 1: Biocapacity digital twin solutionThe hack team “Biohackers” addressed biocapacity, which refers to a biologically productive area’s (cropland, forest, and fishing grounds) ability to generate renewable resources and to absorb its spillover waste. Countries consume1.7 global hectares per personof Earth’s total biocapacity; this means we consume more resources than are available on this planet.To help solve this problem, the team created a digital twin architecture (Figure 1) to virtually represent biocapacity information in various conditions:The Satellite Image Rekognition Module (SIRM) receives biocapacity data from thesustainability category of the Registry of Open Data on AWSdatasets and customer on-premises servers viaAWS Storage Gateway. SIRM also receives ground data from satellite images, which are processed usingAmazon Rekognition, and the data is stored inAmazon Simple Storage Service (Amazon S3).The Biocapacity Intelligent Forecasting Module (BIFM) combines biocapacity data and extracted satellite images usingAWS Glue.Amazon Forecastpredicts biocapacity risk information like fishing or built-up land.The forecast optimization module (FOM) analyzes the biocapacity risks and shows possible actions that can be taken to improve.Amazon Elastic Compute Cloud (Amazon EC2)provides a virtual representation of the current and future biocapacity information to users usingAmazon CloudFront.Figure 1. Biocapacity digital twin solution on AWSThis solution provides precise information on current biocapacity and predicts the future biocapacity status at country, region, and city levels. The Biohackers aim to help governments, businesses, and individuals identify options to improve the supply of available renewable resources and increase awareness of the supply and demand.Architecture 2: Local emergency communication systemTeam “Sustainable Force 99,” worked to better understand natural disasters, which havetripled over recent years. Their solution aims to predict natural disasters by analyzing the geographical spread of contributing factors like extreme weather due to climate change, wildfires, and deforestation. Then it communicates clear instructions to people who are potentially in danger.Their solution (Figure 2) uses theAmazon SageMakerAI prediction model and combines The Weather Company data with Amazon S3,Amazon DynamoDB, andServerless on AWStechnologies and communicates with the public by:Providing voice and chat communication channels usingAmazon Connect,Amazon Lex, andAmazon Pinpoint.Broadcasting alerts across smartphones and speakers in towns to provide information to people about upcoming natural disasters.Allowing individuals to notify emergency services of their circumstances.Figure 2. Local emergency communication systemThis communication helps governments and local authorities identify and communicate safe relocation options during disasters and connect with nearby relocation assistance teams.Architecture 3: Intelligent satellite image processingTeam “Green Fire” examined how to reduce environmental problems caused by wildfires.Many forest service organizations already use predictive tools to provide intelligence to fire services authorities using satellite imaging. The satellites can detect and capture images of wildfires. However, it can take hours to process these images and transmit and analyze the information, which can mean the subsequent coordination and mobilization of emergency services can be challenging.To help improve fire rescue and other emergency services coordination and real-time situational awareness, Green Fire created a serverless application architecture (Figure 3):The drone images, external data feeds from AWS Open Data Registry, and the datasets from The Weather Company are stored in Amazon S3 for processing.AWS Lambdaprocesses the images and resizes the data, and the outputs are stored in DynamoDB.Rekognition labels the drone images that identify geographical risks and fire hazards. This allows emergency services to identify potential risks, and they can further model the potential spread of the wildfire and identify options to suppress it.Lambda integrates the API layer between the web user interface and DynamoDB so users can access the application from a web browser/mobile device (mobile application developed using AWS Amplify).Amazon Cognitoauthenticates users and controls user access.Figure 3. Intelligent image processingThe team expects this solution to help prevent loss of human lives, save approximately 10% of yearly spend, and reduce CO2 emissions globally between 1.75 to 13.5 billion metric tons of carbon.Architecture 4: Machine-learning-based solution to predict bee colonies at riskVariations in vegetation, rising temperatures, and use of pesticide are significantly destroying habitats and creating inhospitable conditions for many species of bees. Over the last decade, beehives in theUS and Europe have suffered hive losses of at least 30%.To encourage the adoption of sustainable agriculture, it is important to safeguard bee colonies. The “I BEE GREEN” team developed a device that contains sensors that monitor beehive health, such as temperature, humidity, air pollutants, beehive acoustic signals, and the number of bees:AWS IoT Core for LoRaWANconnects wireless sensor devices that use the LoRaWAN protocol for low-power, long-range comprehensive area network connectivity.The sensor and weather data (from AWS Open Data Registry/The Weather Company) are loaded in Amazon S3 and transformed using AWS Glue.Once the data is processed and ready to be consumed, it is stored on the S3 bucket.SageMaker consumes this data and generates forecasts such as estimated bee population and mortality rates, probability of infectious diseases and their spread, and the effect of the environment on beehive health.The forecasts are presented in a dashboard usingAWS QuickSightand are based on historical data, current data, and trends.The information this solution generates can be used for several use cases, including:Offering agricultural organizations information on how climate change impacts bee colonies and influences their business performanceContributing to beekeepers’ understanding of the best environment to safeguard bee biodiversity and when to pollinate cropsEducating farmers on sustainable methods of agriculture that reduces threat to beesThe I BEE GREEN device automatically counts when bees are entering or exiting the hive. Using this, farmers can assess a hive’s acoustic signal, temperature, humidity, the presence of pollutants, classify them as normal or abnormal, and forecast the potential risk of abnormal mortality. The I BEE GREEN team aims for their device to deploy quickly, with minimal instructions anyone can implement.Figure 4. Machine-learning-based architecture to predict bee colonies at riskConclusionIn this blog post, we showed you how IBM hackathon teams used AWS technologies to solve sustainability-related challenges.Ready to make your own?Visit oursustainability pageto learn more about AWS services and features that encourage innovation to solve real-world sustainability challenges. Read more sustainability use cases on theAWS Public Sector Blog.TAGS:Customer Solutions,SustainabilityDhana VadivelanDhana Vadivelan is an EMEA Partner Solutions Architecture Leader based in London. He has over 20 years of experience in helping enterprise customers with their IT transformation programs through designing and implementing resilient architectures. He joined AWS a year ago and is leading a team of senior architects that enable partners to develop joint solutions, build technical capabilities, and steers them through the execution phase, as customers migrate and modernize their applications to AWS. He is passionate about enabling customers and partners to adopt cloud-native technologies to solve various business challenges and guide them through their transformation journey. Outside of work, he enjoys spending time with his family, watching movies, some cricket, and traveling on countryside.Markus GraulichMarkus Graulich is the Chief Architect for Artificial Intelligence at IBM Consulting in EMEA. He has 32 years of experience at IBM with a focus on AI and Application Architectures. Markus works with clients, IBM colleagues, and leading business partners in the AI space such as AWS to best meet the needs of IBM clients. He is also involved in conducting learning events and hackathons across IBM, e.g., the recent “Sustainability Applied” hackathon in EMEA.Vlad ZamfirescuAs part of the IBM WW Advanced Analytics Center of Competence, Vlad helps IBM clients break new ground using data science, machine learning, and cognitive computing technologies as a Lead Architect for some of the biggest enterprises around the world. He also provides technical leadership to IBM global clients and IBM practitioners alike through his active involvement in the development of methodologies, frameworks, and technical accelerators within IBM.
This post was co-authored by Dhana Vadivelan, Senior Manager, Solutions Architecture, AWS; Markus Graulich, Chief Architect AI EMEA, IBM Consulting; and Vlad Zamfirescu, Senior Solutions Architect, IBM Consulting Our consulting partner, IBM, organized the “Sustainability Applied 2021” hackathon in September 2021. This three-day event aimed to generate new ideas, create reference architecture patterns using AWS […]
Dhana Vadivelan
Architecture AWS Partner Network Customer Solutions Sustainability