BGMTech
Connected Solutions
IoT & Systems
From sensor to insight
01Sensors
02Edge Gateway
03Data Pipeline
04Dashboard
05Alerts
06Analytics
IoT & Embedded Systems in 2026
Systemsthatsense,decide,
andactontheirown.
We build with ESP32 — the same hardware and protocols running smart factories, environmental monitoring, and industrial automation worldwide.
Why Custom IoT
Off-the-shelf sensors give you data. Custom systems give you control.
Here's what happens when you treat IoT like a weekend project.
“We’ll use a Raspberry Pi”
HoverTap to flipUntil your prototype works on a desk but can’t survive factory temperatures, power fluctuations, or 24/7 operation. A Pi is a dev tool — production needs industrial-grade hardware.
“Just connect it to WiFi”
HoverTap to flipUntil your sensors are in a metal enclosure, underground, or 200 meters from the nearest access point. Real IoT uses LoRa, Zigbee, cellular, or wired protocols — chosen by environment, not convenience.
“We’ll store everything in the cloud”
HoverTap to flipUntil your bandwidth bill exceeds the hardware cost and a network outage means zero visibility. Edge computing processes data locally and syncs when connected.
“Sensors are plug and play”
HoverTap to flipUntil you discover calibration drift, signal noise, and the fact that your temperature sensor reads 3°C too high near the motor. Sensor data needs validation, filtering, and context.
“We’ll build the dashboard later”
HoverTap to flipUntil your operators are staring at raw MQTT messages trying to figure out if 78.1°C is normal for pump #3. The dashboard IS the product for everyone who isn’t an engineer.
“One firmware, ship it”
HoverTap to flipUntil a bug in the field requires physically visiting 200 devices. OTA updates, rollback capability, and remote diagnostics aren’t optional — they’re how you survive deployment.
We're not against prototyping fast. But when you need production-grade reliability, remote management, and real-time intelligence, that's where we come in.
Our Approach
How we connect
Hardware-aware engineering
We pick the hardware for the environment, not the lab.
ESP32 for cost-effective wireless sensing. Arduino for rapid prototyping and custom peripherals. Raspberry Pi for edge computing that needs a full Linux stack. Industrial PLCs when you need certified reliability. We don't have a favorite chip — we have a favorite question: what does the deployment site actually look like?
Data is processed at the edge, not just forwarded.
Sending every raw reading to the cloud is expensive and fragile. We build edge processing that filters noise, detects anomalies locally, and only sends what matters. When the network goes down, your system keeps logging. When it comes back, it syncs. No data gaps, no blind spots.
Edge-first architecture
Predictive, not reactive
Your system tells you what's coming, not just what happened.
We train ML models on your sensor data to detect patterns that precede failures. A bearing that's going to seize, a compressor that's losing efficiency, a coolant loop that's trending toward overheat — flagged hours or days before it becomes an incident. Predictive maintenance turns reactive firefighting into scheduled service.
The Stack
What your system runs on
HWHardware & Embedded
ESP32
Arduino
Raspberry Pi
KiCad
C++
Python
Linux
Go
Rust
Node.js
TypeScript
FastAPI
ESP32
Arduino
Raspberry Pi
KiCad
C++
Python
Linux
Go
Rust
Node.js
TypeScript
FastAPI
ESP32
Arduino
Raspberry Pi
KiCad
C++
Python
Linux
Go
Rust
Node.js
TypeScript
FastAPI
>>Protocols & Data
MQTT
InfluxDB
PostgreSQL
Redis
Kafka
RabbitMQ
Elasticsearch
MongoDB
Grafana
Prometheus
N8N
GraphQL
MQTT
InfluxDB
PostgreSQL
Redis
Kafka
RabbitMQ
Elasticsearch
MongoDB
Grafana
Prometheus
N8N
GraphQL
MQTT
InfluxDB
PostgreSQL
Redis
Kafka
RabbitMQ
Elasticsearch
MongoDB
Grafana
Prometheus
N8N
GraphQL
$Infrastructure & DevOps
Docker
Kubernetes
Terraform
Ansible
AWS
GCP
Git
GitHub
GitLab
Nginx
Cloudflare
Vault
Docker
Kubernetes
Terraform
Ansible
AWS
GCP
Git
GitHub
GitLab
Nginx
Cloudflare
Vault
Docker
Kubernetes
Terraform
Ansible
AWS
GCP
Git
GitHub
GitLab
Nginx
Cloudflare
Vault
The Process
From sensor to insight
01
Discovery
- Environment audit
- Sensor selection
- Protocol planning
02
Prototype
- Hardware setup
- Firmware development
- Sensor calibration
03
Connect
- Protocol integration
- Edge processing
- Cloud pipeline
04
Dashboard
- Real-time monitoring
- Alert rules
- Historical trends
05
Deploy
- Field testing
- OTA updates
- Predictive models
01
Discovery
- Environment audit
- Sensor selection
- Protocol planning
02
Prototype
- Hardware setup
- Firmware development
- Sensor calibration
03
Connect
- Protocol integration
- Edge processing
- Cloud pipeline
04
Dashboard
- Real-time monitoring
- Alert rules
- Historical trends
05
Deploy
- Field testing
- OTA updates
- Predictive models
Your Visibility
Every sensor, every reading. In real time.
01
Live Sensor Dashboard
Every sensor, every reading, every alert — visible in real time on a shared Grafana dashboard. You see what your system sees, not a summary report from last week.
02
OTA Update Pipeline
Firmware updates deploy over the air with staged rollouts. 10% of devices first, then 50%, then all. Automatic rollback if error rates spike. No truck rolls for bug fixes.
03
Predictive Maintenance Alerts
ML models trained on your sensor data detect anomalies before they become failures. Get notified 48 hours before a bearing needs replacement, not after it seizes.
04
System Documentation
Wiring diagrams, protocol specs, firmware architecture, deployment runbooks. Your maintenance team can operate and extend the system independently.
Architecture
How an IoT system comes together
Devices
ESP32ArduinoRaspberry PiIndustrial PLCs
Protocols
MQTTCoAPLoRaModbusBLE
Edge
Local ProcessingData FilteringAnomaly DetectionBuffering
Cloud
InfluxDBPostgreSQLTimescaleDBS3
Dashboard
GrafanaCustom UIAlertsHistorical Trends
99.7% Uptime50+ Sensors5 ProtocolsEdge + Cloud
Device Layer
Your devices report in. Automatically.
Every device in the field registers itself, reports health status, and accepts firmware updates over the air. No manual provisioning, no spreadsheet of IP addresses.
When a sensor goes offline, the system knows immediately — and routes alerts based on severity, location, and impact. Critical failures page on-call. Intermittent drops log and auto-retry.
Your fleet of 5 devices or 500 is managed from one dashboard, one firmware pipeline, one source of truth.
device-manager — fleet/prod
6 devices onlineESP32-TH-01online
Temp + HumidityESP32-VIB-03online
Vibration SensorRPi-EDGE-01online
Edge GatewayARD-FLOW-02online
Flow MeterESP32-PRESS-01alert
Pressure Sensorfleet: healthyOTA: ready
firmware pipeline v3mqtt-monitor — factory/floor-2
$ mqtt-monitor --subscribe sensors/#
[temp-01] 23.4°C ✓ normal
[humid-01] 61.2% ✓ normal
[press-01] 1013hPa ✓ normal
[vibe-03] 0.12g ✓ normal
[temp-07] 78.1°C ⚠ threshold exceeded
→ Alert dispatched: maintenance team notified
→ Predictive model: bearing replacement in ~48h
5 sensors ✓ | 1 alert | uptime: 99.7%
Live MonitoringEvery reading, every second.
Every reading, every second.
Before it becomes a problem.
MQTT streams sensor data in real time to your monitoring stack. Temperature, humidity, vibration, pressure, flow — whatever your environment measures, we capture, validate, and visualize it.
Threshold-based alerts catch the obvious. ML-based anomaly detection catches the subtle — the patterns that precede failures by hours or days.
Your operations team sees what's happening now AND what's likely to happen next.
By The Numbers
0+Sensors Managed
0.7%System Uptime
0+Dashboards Built
0/7Monitoring
<0hPredictive Alerts
YOUR PROJECT HERE
Be the first to highlight your project with us.
We're looking for our first IoT case study. If you have a sensor network, monitoring system, or industrial automation challenge — let's build it together and showcase the results.
Start the ConversationLet'sconnectyourworld.
Tell us what you need to monitor, automate, or predict. We'll tell you how we'd build it — from sensor to dashboard.