Global IoT DevFest III

Developing Smart City - Open Data & AI


Only using current Open Source solutions, we show best practices for implementing Smart Cities, across Things' cameras and sensors to Gateway to Cloud, emphasizing open build scripts, security and DevOps lifecycle, a Reference Architecture with compliance for US, India, China and European Smart Cities. Solutions include (in demo build order):

1. Platform infrastructure with RASS (Reliable, Available, Safe and Secure): Kubernetes orchestration of trusted pods of Docker containers, with Kafka publish-subscribe containerized microservices (city data & AI, cloud lambda, 5G directory services). Cloud: Amazon S3 frontend, using Pithos compatible API, ensuring local gateway data governance, compliance and control.

2. Control plane with Dimension Remote AAA (Authorization, Authentication and Accounting): publish and subscribe ledger-assured city services, for compliance, billing and payment. Monitor: Helm and Collectd with cAdvisor plug-in for monitoring and log generation. ELK: Elasticsearch v6.2, with Logstash and Kibana plug-ins for scalable log handling and viewing.

3. Data plane with CIAP (Confidential, Integrity, Audit and Privacy): InfluxDB spatial and time series, for Digital Twin correlating who, what, when and where, including feeding AI. AI: Tensorflow neural net with Python-Skit, inference engine and OpenCV computer vision for facial and license plate recognition, hosting images, video and non-scalar data. Scale: Spark cluster, extremely scalable, fast, and local so no network bottlenecks


You must be logged in and own this session in order to post comments.