Real-time video analytics can be used for a wide range of use cases across industries:
- Retail: monitor foot traffic within a store to optimize product placement, enhance loss prevention measures, or display personalized digital promotions
- Financial services: boost security surveillance in bank branches, or display personalized digital promotions at ATMs
- Manufacturing: detect product defects on the production line before they affect an entire batch, or identify when factory workers are missing safety gear
This project demonstrates a deployment of the RedisEdge stack that provides real-time analytics of video streams. It uses Redis Streams, RedisGears, RedisAI, and RedisTimeSeries to count the number of people in a video.
When synchronizing databases, ensure data persistence and availability of captured data changes while mitigating the performance penalty associated with shipping them to the target database.
This example shows how to use the Write Behind pattern to map data from Redis Hashes to MySQL tables. The recipe maps all Redis Hashes with the prefix person:
This demo for RedisGears uses fbprophet for timeseries prediction in anomaly detection.
Content delivery performance is essentially about latency and speed. While content delivery networks (CDNs) offer image optimization solutions and the shortest hop to the user, additional byte savings can be achieved through optimizing memory usage of the image. Doing so saves data on the backend, in client’s devices, and improves delivery performance since fewer bytes require fewer network packets to be transmitted.
This example illustrates how to automatically process, transform, and model different types of data using serverless content delivery optimizer logic with Redis and RedisGears.
Modern applications are increasingly sophisticated, and often rely on multiple databases to deliver expected results. Retrieving data from each database introduces latency, impacting user experience. Using a database that supports multi-models natively dramatically improves application performance.
This step-by-step demo starts from Redis Hash and dynamically adds new models using Redis Modules. The accompanying video illustrates retrieving and synchronizing data across multiple databases to “find the restaurants my friends recommended in my 3-mile radius” and sort by visitor load.
This application was developed as a no-touch alternative to tracking attendance in classrooms, previously done through fingerprinting. It can be applied to any situation where facial recognition is needed. Built using the RedisEdge stack, it is able to process the image data in real time, and easily scales to analyze large groups of people.
According to the CDC, during the COVID-19 pandemic, all healthcare workers must follow strict guidelines and protocols from OSHA regarding wearing PPE. N95 masks are the PPE most often used to control exposure to infections transmitted via the airborne route. Therefore, checking the medical staff’s PPE safety protocol is especially crucial during this pandemic.
This web-based app analyzes video streams and applies a mask detection model to check that the medical staff is following established safety protocols.
The recent shift to virtual learning, for everyone from K-12 to higher education, has forced students, parents, and teachers to change how they approach learning. One area that is still evolving is how to evaluate student performance and achievement. Innovations in both learning and evaluation methods are needed.
This project includes two components. The first is aimed at students—a browser plug-in that transcribes notes from videos and auto-generates quizzes to check comprehension. The second is aimed at educators—a web-based application to upload courses, generate quizzes, and answer student questions.
Many non-profit organizations recruit volunteers through social media. However, managing the lists of volunteers for each event is often done manually, and communicating updates via social media is inefficient. A better way of organizing volunteer activities is needed.
This application automates a number of steps in the process of recruiting and confirming volunteers for events. It also enables organizers to easily communicate with confirmed volunteers to provide timely updates.
This application is a blockchain-based ecommerce platform for buying and selling SPEC tokens without a third party. Since every transaction on a blockchain platform triggers a fee, this application abstracts common, low-value tasks from the platform and performs them within Redis in order to avoid unnecessary fees.
Internet fraud is evolving. The more you try to stop abuse, the more complex methods fraudsters use to trick you. The idea of a real-time fraud detector is not new, but getting it right is a major challenge.
This project identifies different types of fraud in an ad network, then publishes the data for further analysis and visualization.
In e-commerce, a user, on the scale of an application, visits infrequently. Keeping indexes constantly ready for things like past purchases is a waste if the users will only look at this while they are logged in. This shows how to solve the problem by only keeping track of past purchases when users are actually logged into the system. When a user times out, we remove the index and build it in real-time and on-the-fly.
This demo shows a simple e-commerce platform that implements a purchase history that is created on the fly using RediSearch. The abstract concept of ephemeral indexing becomes very visible if run in conjunction with Redis MONITOR.
Pop-up stores are becoming a popular channel for retailers to create a new revenue stream, generate buzz with customers, test product concepts, or unload excess inventory. Since the idea is to spin up the store quickly and then close it shortly thereafter, it doesn’t make sense to spend a lot of time on development. With the right Redis modules, you can create a robust customer experience without a lot of development effort.
This pop-up store demo illustrates a company that sells a single product and has 10,000 units available for purchase. Each customer can purchase one unit and the sale lasts only 10 minutes, so order processing must be instantaneous. The demo shows how to visualize data pipeline in real-time using Redis Streams, RedisTimeSeries, RedisGears and Redis Datasource with Grafana.
Creating a leaderboard can be done in several ways, including using a relational database. However, as the amount of data increases with each additional participant, and the number of queries rise as more users access the leaderboard, scaling and performance become an issue.
This project uses Redis Sorted Sets to create a real-time leaderboard for the India Premier League tournament, showing the batsmen with the highest number of runs.
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SG SGStrings StringsData Structure
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BM BMBitmaps BitmapsData Structure
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BF BFBit Field Bit FieldData Structure
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H HHashes HashesData Structure
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Se SeSearch SearchModule
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Js JsJSON JSONModule
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L LLists ListsData Structure
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S SSets SetsData Structure
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SS SSSorted Sets Sorted SetsData Structure
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Ts TsTimeseries TimeseriesModule
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Bl BlBloomfilter BloomfilterModule
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Ai AiAI AIModule
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G GGeospatial GeospatialData Structure
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HL HLHyperloglog HyperloglogData Structure
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SM SMStreams StreamsData Structure
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Gr GrGraph GraphModule
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Ge GeGears GearsModule
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Is IsInsight InsightModule
Integrated in Redis Enterprise Learn more
Integrated in Redis Enterprise Learn more
Integrated in Redis Enterprise Learn more
Integrated in Redis Enterprise Learn more
Integrated in Redis Enterprise Learn more
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SG SGStrings StringsData Structure
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BM BMBitmaps BitmapsData Structure
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BF BFBit Field Bit FieldData Structure
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H HHashes HashesData Structure
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L LLists ListsData Structure
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S SSets SetsData Structure
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SS SSSorted Sets Sorted SetsData Structure
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G GGeospatial GeospatialData Structure
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HL HLHyperloglog HyperloglogData Structure
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SM SMStreams StreamsData Structure
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Se SeSearch SearchModule
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Js JsJSON JSONModule
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Ts TsTimeseries TimeseriesModule
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Bl BlBloomfilter BloomfilterModule
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Ai AiAI AIModule
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Gr GrGraph GraphModule
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Ge GeGears GearsModule
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Is IsInsight InsightModule
Integrated in Redis Enterprise Learn more
Integrated in Redis Enterprise Learn more
Integrated in Redis Enterprise Learn more
Integrated in Redis Enterprise Learn more
- See how others have already rediscovered Redis
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Real-time Video AnalyticsMonitor traffic, boost security, detect anomalies
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Database Synchronization with PersistenceEnsure persistence and availability of data changes
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Time-series PredictionPredict the possibility of an anomaly before it happens
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Improved Content DeliveryOptimize memory usage of images to boost performance
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Modern Multi-Model ApplicationsReduce latency with multi-model instead of multi-database
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“Facemark” Facial RecognitionA no-touch alternative to tracking attendance in classrooms
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“RediSafe” Image DetectionAutomatically check that personnel is following safety protocols
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“intelliSchool” Student Evaluation ToolUpload courses, auto-generate quizzes, interact with students
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“Voluntree” Event Organization ToolCoordinate volunteers for events more efficiently
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“SpecKart” Blockchain Ecommerce PlatformAbstract common blockchain tasks to avoid transactional fees
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Real-Time Fraud DetectionIdentify different types of fraud and analyze the data
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Real-time IndexingA demo showing a purchase history created on the fly
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Pop-up Store DemoCreate a robust customer experience without a lot of effort
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Real-time LeaderboardsCreate a real-time leaderboard that easily scales
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