{"id":567,"date":"2022-12-24T16:09:26","date_gmt":"2022-12-24T16:09:26","guid":{"rendered":"https:\/\/radicalbit.ai\/?p=567"},"modified":"2026-04-23T08:53:56","modified_gmt":"2026-04-23T08:53:56","slug":"streaming-ml-saved-christmas","status":"publish","type":"post","link":"https:\/\/radicalbit.ai\/it\/resources\/blog\/streaming-ml-saved-christmas\/","title":{"rendered":"How Streaming ML saved Christmas: a use case for Santa\u2019s delivery optimization"},"content":{"rendered":"\n<h3 class=\"wp-block-heading\">Scenario &amp; Challenge<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Christmas is no joke, especially for Santa Claus. Each year Father Christmas has only one night to deliver gifts to the entire world population, which in 2022 reached 8 billion people. Even considering only children and young people under 18, we are talking about 2,3b potential recipients to be visited and given gifts in very few hours \u2013 flying east to west. This is why optimising delivery has become of paramount importance.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This year we have had the lifetime opportunity to team up with Santa\u2019s team in Rovaniemi. Santa\u2019s Office CEE (Chief Executive Elf) asked us to devise a solution for maximising the efficiency of sleigh-based delivery, in order to guarantee a safe and effortless distribution of gifts all around the world.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">We immediately thought of using technology to monitor in real time sleigh and reindeers\u2019 performance, leveraging data to dynamically adjust the gift-delivery strategy. This can be achieved thanks to the combination of connected telemetry sensors and machine learning models to generate descriptive and prescriptive intelligence.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Our Solution<\/h3>\n\n\n\n<h4 class=\"wp-block-heading\">Data Collection<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">Since the year 2000, Santa has started collecting a vast range of gift-delivery data thanks to a sensor-based telemetry system on his sleigh and reindeers.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Data collected can be grouped into 3 categories:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Environment<\/strong>:\n<ul class=\"wp-block-list\">\n<li>Wind Speed<\/li>\n\n\n\n<li>Temperature<\/li>\n\n\n\n<li>Visibility<\/li>\n\n\n\n<li>Precipitation<\/li>\n\n\n\n<li>Altitude above sea level<\/li>\n\n\n\n<li>Oxygen in the atmosphere<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Delivery place conditions:<\/strong>\n<ul class=\"wp-block-list\">\n<li>Presence of chimney<\/li>\n\n\n\n<li>Type of house<\/li>\n\n\n\n<li>Presence of in-house pets<\/li>\n\n\n\n<li>Distance from next delivery place<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Sleigh:<\/strong>\n<ul class=\"wp-block-list\">\n<li>Balancing of transported cargo<\/li>\n\n\n\n<li>Weight of transported cargo<\/li>\n\n\n\n<li>Reindeer energy<\/li>\n\n\n\n<li>Wear of runners<\/li>\n\n\n\n<li>Speed<\/li>\n\n\n\n<li>Temperature on board<\/li>\n\n\n\n<li>GPS<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">The two main challenges to overcome for Father Christmas are:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">1) Assess when he will be able to safely reach the following point of delivery;<br>2) Estimate when he will be able to complete all deliveries.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Thanks to the historical data collected in 22 years, from Christmas 2000 until 2021, Santa Claus was able to label the two targets. This allowed us to create a supervisioned multi-target AI model that is capable of accurately predicting in real time the necessary delivery time. In this way, Santa <strong>can dynamically adjust his delivery speed based on the model\u2019s output.<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-image\"><img fetchpriority=\"high\" decoding=\"async\" width=\"1024\" height=\"1024\" src=\"https:\/\/radicalbit.ai\/wp-content\/uploads\/2023\/11\/blog-post__AIsavedChistmas__img2.webp\" alt=\"\" class=\"wp-image-978\" title=\"blog-post__AIsavedChistmas__img2\" srcset=\"https:\/\/radicalbit.ai\/wp-content\/uploads\/2023\/11\/blog-post__AIsavedChistmas__img2.webp 1024w, https:\/\/radicalbit.ai\/wp-content\/uploads\/2023\/11\/blog-post__AIsavedChistmas__img2-300x300.webp 300w, https:\/\/radicalbit.ai\/wp-content\/uploads\/2023\/11\/blog-post__AIsavedChistmas__img2-150x150.webp 150w, https:\/\/radicalbit.ai\/wp-content\/uploads\/2023\/11\/blog-post__AIsavedChistmas__img2-768x768.webp 768w, https:\/\/radicalbit.ai\/wp-content\/uploads\/2023\/11\/blog-post__AIsavedChistmas__img2-980x980.webp 980w, https:\/\/radicalbit.ai\/wp-content\/uploads\/2023\/11\/blog-post__AIsavedChistmas__img2-480x480.webp 480w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><em>Our study on Santa\u2019s Sleigh and reindeers<\/em><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Data Exploration<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Following Exploratory Data Analysis, it can be seen that all variables collected have an influence on the target. For instance, if Santa\u2019s sleigh is flying at high altitude, the reindeers can experience shortness of breath and thus reduce the speed. If they are tired and flying on low energy levels, they need to stop to rest and eat. If the delivery point lacks a chimney, or a watchdog is in place, dropping the cargo may be more difficult and thus time consuming.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Deep Learning Model<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">After exploring the variables, we worked with Santa to develop a deep learning mode, called Christmas-Net-V1, that was trained on the huge amount of available historical data. The model delivered outstanding performance with the two targets:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Prediction of next gift delivery time with 1,4 \u03bcs MAE (Mean Absolute Error)<\/li>\n\n\n\n<li>Prediction of time remaining for delivery completion with 15 \u03bcs MAE (Mean Absolute Error)<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">Enrich real-time data with AI (and save Christmas)<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">We used our MLOps Platform to combine the streaming data from Santa\u2019s sensors and the Christmas-Net-V1 model. Radicalbit\u2019s Platform&nbsp;is a codeless Data for AI &amp; MLOps solution that allows data teams to deploy, serve and monitor ML models effortlessly, <strong>driving productivity and reducing time to market<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The platform core lies in the streaming, MLOps and pipelining capabilities. The first concerns the collection of real-time data from external sources such as IoT &amp; telemetry systems; the MLOps section enables the model serving and monitoring; the visual pipelines editor defines the operations, both preset and custom, that are to be performed on the flowing data.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In our Christmas use case, data collected by sensors are fed into a Kafka topic as soon as they are generated, to be then processed by a pipeline that moves data forward and transforms them in the way required by the model input.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Finally, a series of&nbsp;<strong>webhooks alert in real-time<\/strong>&nbsp;the on-board navigation system when certain conditions are met and Santa must revise the delivery route by accelerating, making a detour, etc.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Conclusion &amp; Next Steps<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">We are proud to have worked with Santa and his team to develop a reliable solution to ensure a timely gift delivery and increase the Christmas spirit. This year,&nbsp;<strong>event stream processing and machine learning will play a role in making children\u2019s wishes come true<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">We will keep on evolving our MLOps-powered solution to include more functionalities, further reinforcing the integration with Santa\u2019s technological stack. In particular, we are working to make our solution compatible with the ML-enabled decision support system that augments Santa\u2019s capacity to make a list, check it twice, and find out who\u2019s naughty or nice. In this way, the gift delivery route will be modified in real time based on last-minute reconfigurations of the list.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If you want to learn more about our MLOps Platform and the way in which it can help your business enhance decision making with artificial intelligence and streaming data,&nbsp;<a href=\"https:\/\/radicalbit.io\" target=\"_blank\" rel=\"noreferrer noopener\">visit our website<\/a>&nbsp;and start your free demo.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In the meantime, the Radicalbit team wishes you a&nbsp;<strong>very special Christmas and a wonderful new year!<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>This Christmas we teamed up with Santa to maximise the efficiency of sleigh-based delivery, for a safe and effortless gifts distribution worldwide. We immediately thought&hellip;<\/p>\n","protected":false},"author":1,"featured_media":3366,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[28,30],"tags":[21,49,22,68,67,69],"class_list":["post-567","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog","category-by-radicalbit","tag-ai","tag-christmas","tag-decision-intelligence","tag-ml","tag-santa","tag-streaming-data"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>How Streaming ML saved Christmas: a use case for Santa\u2019s delivery optimization | Radicalbit<\/title>\n<meta name=\"description\" content=\"This Christmas we employed Streaming ML in our MLOps platform leveraging data to help Santa in his sleigh-based delivery activities.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, 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