Editor’s note: In this guest blog we look at how a Sensor AI solution provider uses Google Cloud to deliver highly scalable and reliable SaaS solutions across the globe.
SenSen has become the world leader in Sensor AI technology-based solutions thanks in large part to Google Cloud.
Sensor AI is the branch of AI that deals with the analysis and fusion of data from multiple sources including cameras, GPS, Radar, Lidar, IoT devices, GIS databases and transactional data to solve problems that defy traditional methods.
SenSen’s AI platform SenDISA uses Google Cloud for machine learning training and inferencing at scale for the benefit of municipalities, transport authorities, retailers, casino operators, and others to automate monotonous, laborious activities within their operations and gain insights that are impossible to obtain from one data source alone.
SenDISA is a distributed platform designed to deliver solutions at scale for public and private enterprises. The platform components are distributed between on-premise edge computers and those that are cloud-powered by Google AI Cloud services.
Google Cloud supports global growth
The success of SenSen’s solutions has taken the company to all corners of the world. The company now supplies highly reliable, scalable, and differentiated solutions across four continents. When clients need insights fast, SenSen often has to initiate pilot programs and roll out full-scale production deployments rapidly and at short notice. That means being nimble and responsive. And at the same time, the company has to ensure it maximizes its technology investments.
SenSen has been using Google Cloud for more than a decade to deliver AI solutions at scale worldwide —quickly, simply, and cost-effectively. Today, it relies on a variety of Google Cloud solutions including Compute Engine, Cloud TPU, Cloud SQL, and operations suite to power its growing business.
Compute Engine and Cloud TPU are the foundation for all cloud processing and analytics functions. Compute Engine allows the creation and running of virtual machines (VMs) to support a wide range of applications.
SenSen relies on Cloud TPU to run its machine learning models. This ensures high performance for all compute-intensive analytics. And it uses Google Cloud’s operations suite to closely monitor all of its Google Cloud services for full visibility into the health and status of its platform infrastructure.
With Compute Engine and Cloud TPU, SenSen can spin up VMs and configure TPU clusters on-demand with minimal effort. And expanding capacity or extending functionality is fast and easy, including managing storage requirements in Cloud SQL.
With Google Cloud environment, SenSen gets to minimize upfront investments, tightly align recurring expenses with evolving business demands, and free up development resources to focus on intellectual property rather than underlying infrastructure.
Google Cloud also makes it easy to ensure high availability for safety-critical applications like surveillance deployments where system downtime could lead to illegal activity, accidents, or even loss of life. Delivering predictable and dependable services greatly helps SenSen increase customer retention, grow ARR, and improve business results.
Selecting the right partner
SenSen chose Google Cloud based on its pioneering status as an early and leading provider of AI technology and cloud services.
With most of SenSen’s products using Tensorflow framework and relying heavily on GPIs, Google has the most robust and leasing AI framework offering:
- Cloud TPU training that is extremely powerful and easy to use
- Seamless integration of GCS buckets and the AI platform
- Seamless integration of Tensorflow framework
- Wide range of GPU architectures to choose from
- Fast and efficient creation on VMs
- Capable on launching model training on the fly, and also TPU clusters
GIS services at the heart of positioning and context setting
SenSen was an early adopter of Google’s geocoding services – Google maps and other GIS services – for address lookup with GPS used for enforcement purposes.
Google Maps helps SenSen locate on-road enforcement devices as well as offending vehicles that have overstayed parking limits or parked illegally.
When patrolling urban areas, Google’s location API is used in web dashboards for easy searching of enforcement zones loaded into the system. This work is made easier by Google’s polygon drawing API which helps draw enforcement polygons that capture all the zones in a modern urban area including No Parking, No Stopping, Clearways, Bus Lanes, Transit Lanes, Cycling Lanes and all types of parking time limits.
Throughout SenSen’s evolution, Google’s GIS-based services have been unique, comprehensive and easy to use in delivering a great experience to end customers.
Transforming diverse sensor data into previously unachievable business insights
SenSen’s mission is to positively transform people’s lives with Sensor AI. Unlike other analytics solutions that narrowly focus on a single type of sensor data, SenSen’s SenDISA platform intelligently analyzes and fuses data from a wide array of sources including cameras, GPS, Lidar, Radar and other location sensors, motion sensors, and temperature sensors, and other IoT devices to deliver insights that are otherwise impossible to obtain. Using fused data, the company is able to solve a variety of use cases across multiple industries.
Example applications include:
- Road safety – help cities save lives through detection and enforcement of dangerous driving practices including speeding and distracted driver behavior.
- Congestion – in urban areas SenSen reduces congestion and improves the citizen parking experiences
- Theft reduction – the company help fuel retailers reduce fuel theft and improve safety for their employees and customers
- Casinos – helps casino operators improve compliance and customer experiences.
- Surveillance – helps surveillance operators be productive and efficient in detecting, tracking and managing incidents.
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By Subhash Challa Founder & CEO, sensen.ai
Source Google Cloud Blog