Smart sensors
Edge IoT • Smart Sensors • Predictive Analytics • Custom Software
IoT based Smart Sensor Solutions often need to be deployed at the Edge so as to avoid latency in decision making and data transfer.
At a glance
- Edge-first architecture for real-time control
- Horizontal framework + vertical accelerators
- UI/UX + .NET + Angular + SQL expertise
About Services
Custom software development for Smart sensors
What is Smart Sensors
Such Edge IoT Solutions offer a paradigm shift but they also need to be architectured well to address a gamut of use cases from Oil & Gas and Manufacturing to Mining and Water Management.
Our Expertise
Pre-trained ML models are deployed at the Edge to maximize the benefits of predictive analytics.
Our Solution
A Horizontal Framework provides a common abstraction layer; vertical accelerators plug in cleanly on top.
Case Study
Interactive PCP Visualization
Customer: Kelvin (San Francisco) • Domain: Oil & Gas • Team: 4 • Timeline: 6 months
Kelvin is a San Francisco based company that focuses on building a AI-based, Next Generation platform for Control Systems. They have a suite of products that offer everything from Visualization, Simulation, Collaboration and Decision-making for a plethora of domains including Oil & Gas, Manufacturing, Food & Beverage, Mining and Renewables. With their current Product Management & Engineering bandwidths severely constrained, Kelvin was looking for help to create an interactive Visualization Tool for a use case based on Oil & Gas, Progressive Cavity Pumps.
Customer Challenge
- Needed quick PCP Module developed
- With severely constrained Engineering bandwidth, Kelvin was looking for help for an Visualisation Tool for a Customer Pilot
What We Did
- WonderBiz put together a new team at short notice
- With little or no specifications, the team with UI / UX skillsets began hashing out the interface, taking full ownership of User interactions.
Dashboard view from Kelvin PCP Visualization module
Outcome
Pilot Module made an impact with the end Customer.The Module paved the way for Kelvin to successfully conclude a Pilot engagement with one of their customers.
Case Study — Predictive Maintenance for Chiller Plants
Customer: Facility Ops (APAC) • Domain: HVAC & Energy • Team: 5 • Timeline: 4 months
A multi-site facilities operator needed a unified edge-first solution to stream real-time sensor data from chillers, detect anomalies, and recommend energy-saving set-points—without risking latency or cloud outages.
Customer Challenge
- Fragmented BMS data and no common data model.
- Manual alarms; frequent false positives.
- Zero downtime tolerance across critical sites.
What We Did
- Built an edge gateway with buffering + offline-first sync.
- Deployed pre-trained anomaly models for chillers and pumps.
- Delivered a role-based dashboard with actionable insights.
Predictive maintenance dashboard for HVAC assets
Outcome
Sites saw measurable energy reduction and fewer false alarms. The team adopted data-driven maintenance windows, cutting unplanned downtime.
Technology
Chosen for speed, stability, and scale.
Robust SPA framework for fast, type-safe frontends with RxJS and enterprise tooling.
High-performance APIs and services with ASP.NET Core and cloud-native patterns.
Reliable transactional storage, analytics-ready schemas, and tuned query performance.
Testimonial
“One of the strongest aspects of the WonderBiz team was communication. They were clear and transparent, asked the right questions, and quickly identified who on our side could help resolve blockers.
We received tremendous value from WonderBiz in being able to spin up a capable team on short notice, delivering results that supported our Customer trial and positioned us for an exceptional project ahead.”
Testimonial
“The WonderBiz team brought strong technical depth to our predictive maintenance initiative — edge gateways, buffered sync, and pre-trained anomaly models all worked reliably across sites. Their engineering rigor reduced false alarms and helped us implement energy-saving set-points safely.
Their cross-functional approach (embedded engineers + data scientists + platform team) made deployment rapid and maintainable.”
Connect with our experts
A quick discovery call to understand goals, constraints, and success metrics—then map your fastest path to a results-driven pilot.
- Architecture outline & PoC plan
- Timeline, team composition, and cost range
- Transparent scope and delivery milestones