AI Driven Wi-Fi for the Bottom of the Pyramid
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AI Driven Wi-Fi for the Bottom of the Pyramid
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AI Driven Wi-Fi for the Bottom of the Pyramid
- 1. AI Driven Wi-Fi for the Bottom of the Pyramid BDNOG 17, 12 Dec – 15 Dec 2023 Mainul Hasan Alin, Founder, Janata Wi-Fi
- 2. Our Journey • Built Wi-Fi Cloud that cost 1/10th of a big vendor enterprise WIFI system. • Innovated in distribution, partnered with ISPs, DFS and Merchant networks. • Innovated on Business Model, Advertisement Based Free Wifi. • Innovated on edge network automation • Funded by APNIC Grant, Microsoft & Private Funding
- 3. Public Wifi Experiments • Mixture of Tea Stall, Mudi Dokaan & Bkash Shops • Device is typically hosted within the shop • Some of the nodes have very high concurrent usage • Mobile App based device activation CASE STUDY: PERFORMANCE IN RAINKHOLA MIRPUR • Operates 10 hours a day on average. • Monthly 1000+ Ad views. • Monthly 100+ Voucher Sold. • Merchant gets USD .0025 per Ad view and USD .01 per voucher. Internet Connection • 30-50 Meter Range • 25 User Capacity ISP
- 4. Operational Challanges High Reliability Connections are Expensive. Requires human interventions. Average issue solving time is 10+ Hours. Power failure is rampant with high cost of fuel. Expensive Access Points. Operation & Management for hundreds of Wifi Zones.
- 5. RETAIL CUSTOMER SERVICE CHALLENGES in BANGLADESH Call SMS Digital Others • Billing, Package, Inquiry: Take Note • Fiber Movement, Bent/Cut: Physical Support • Majority, Bandwidth Related: Remote and Physical Support 5 minutes to pick up 3 Hours For Remote Support to Call 10 Hours+ For Physical Support to Arrive Call Center Remote Support Physical Support • Collects Data • Debugs and Solves • Or, forwards to Physical Support • Or, non issue, convinces customer • Challenges • Users sometimes cant tell what is ONU and what's its status. • Remote access for command line data collection requires a bit sophisticated users. Its time consuming. 30 Minutes For Remote Support to Collect Data • Fixes Fiber • Restart Router, Some Config(Reset, Change Admin/SSID user pass, wifi channel, OS upgrade) • Advice Customer on Changing from Old Router • Advice Customer on Placing the Router from Right Place • Challenges • Convincing customer that it’s a issue with old hardware • Not many smart support engineers that can debug quick.
- 6. RETAIL CUSTOMER SERVICE AUTOMATION – Customer Interface 1 Minute to Navigate 2-5 Minute to Collect Data 2-5 Minutes to Resolve Issue
- 7. Base Architecture Client APPs APs State Events Logs Metrics Packet Capture Topology Sessions Data Warehouse AI/ML Engine Packet Metadata Logs Topology Application Layer Test Results Baselining Anomaly Detection Classification Matching Root Cause Analysis Solution Suggestion Auto Deployment Confirmation OLT ONU BRAS
- 8. AI & ML Tools & Techniques • Anomaly Detection • For Time Series Data • First Need to Establish a Baseline, then look for anomalies • Large Language Models • Very Good at explaining unstructured data. • Works as a CoPilot to the Network Support Engineer.
- 9. CXM System – Network Co-Pilot Dashboard Co-Pilot For Visual Queues As an Issue Debugging Assistant
- 10. Future Directions • Data Collection from Non Conventional Agents. • Work on Automated Solution Deployment and Confirmation • Machine learning • Automated issue detection and fixing • Wifi Sensing • Challenge: AI Talent is Expensive