Projects
Reference project · IoT, networking & digital signage

Smartenic

Sensors connected, readings transmitted in real time, network and backend, central management of the displays.

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  • Operation including hardware replacement
  • Planned and built for your business
Smartenic
The short answer

What is the Smartenic platform, and who developed it?

The Smartenic platform collects sensor data from building systems and centrally controls digital displays, aimed at smarter building management. NDVDL developed the sensor connectivity that feeds data into the platform, the real-time data transmission over the MQTT protocol, a Python backend that processes and prepares the incoming sensor data, and the digital signage management system that centrally controls the displays. The design is publish/subscribe: many sensors can send data at once without the platform having to actively poll each one individually. Sensor data and display control therefore run on one shared platform rather than as separate systems.

Our role at Smartenic

Smartenic brings building services and digital displays together: sensors deliver readings from the building, digital displays show content, and both are meant to run on a shared platform instead of separate islands.

NDVDL supports this on three levels: IoT — connecting the sensors and transmitting their readings in real time —, the network over which sensors, displays and backend talk to each other in the first place, and the digital signage management used to control the displays centrally. The cooperation is ongoing, not limited to a one-off project.

Starting point

Smartenic needed a platform that captures sensor data from building services and controls digital displays centrally — for smarter building management. NDVDL supports this across IoT, networking and digital signage.

Project scope

What we did

IoT sensor integration

Connecting sensors from the building systems to the platform.

Data transfer via MQTT

Real-time transfer of sensor data over the MQTT protocol.

Backend in Python

Processing and preparing the sensor data in the Python backend.

Digital signage management

Central system for controlling digital displays throughout the building.

Networking & connectivity

Network-side connection of sensors, displays and backend so readings and content reliably arrive.

The technical details are project-specific — we're happy to walk through the exact implementation in person.

How it works

From analysis to day-to-day operation

No off-the-shelf project — a clear path to IT you can rely on.

  1. 01

    Initial Consultation & Analysis

    We take a look at your IT — free of charge and with no obligation. You get an honest assessment: what's good, what's missing, what's risky.

  2. 02

    Concept & Offer

    You receive a concept tailored precisely to your business — explained in plain language, without jargon and without hidden line items.

  3. 03

    Implementation

    We build your infrastructure — cleanly documented and with minimal disruption to your day-to-day operations.

  4. 04

    Operation & Full Service

    After installation is when we really get started: monitoring, maintenance, optimization — and hardware replacement when something fails, if you want it.

The technical stack

IoT sensor connectivity

Connects sensors from the building's technical systems to the platform.

Building sensor hardware is rarely a single uniform system — sensors come from different manufacturers and speak different protocols. The connectivity layer has to map that variety onto one common interface so downstream systems can work with a consistent data format.

MQTT

Transmits sensor data to the backend in real time.

MQTT is a publish/subscribe protocol built for many devices sending data at once over limited bandwidth — unlike HTTP polling, it doesn't require continuously asking whether new data is available. That reduces network load and holds up better against short connection drops, since MQTT brokers can queue messages until a device reconnects.

Python

Processes and prepares the incoming sensor data in the backend.

Python offers a wide ecosystem of libraries for handling time-series data and adapts quickly to new sensor types or data formats. For a backend that continuously processes data from heterogeneous sources, that flexibility matters more than raw execution speed.

Digital signage management

Centrally controls the building's digital displays.

Signage devices in a building run without continuous on-site supervision and need to receive and display content reliably, even when individual devices are temporarily unreachable. A central management system lets content and device status be controlled and monitored from one place instead of maintaining each display individually.

Networking

Connects sensors, displays and backend with each other.

IoT rarely fails at the sensor and often at the network behind it: devices have to be reachable, their data has to find its way to the backend, and displays have to fetch their content reliably. A properly planned and segmented network is therefore not a side issue but the precondition for the platform running stably inside the building.

What makes an IoT sensor platform for building systems technically demanding

Building sensor hardware continuously produces data from potentially many devices at once — and those devices aren't always reachable. Transmission over HTTP polling would mean actively querying every sensor at fixed intervals regardless of whether anything changed, which creates unnecessary network and server load. MQTT solves this with a publish/subscribe model: sensors send values as they occur, and the backend subscribes to the relevant topics without having to ask. During the brief connection drops that happen on building networks, MQTT brokers can hold messages rather than lose them.

The second requirement concerns display control: digital signage devices run unattended in the building and need to receive content reliably even when a device is briefly offline or restarting. That calls for a control layer that tracks the status of every device and redelivers content rather than silently assuming a display is current. Combined with the sensor-data processing in the backend, the result is a platform that has to serve two different real-time demands — incoming sensor data and outgoing display content — on one shared foundation.

Technical questions about this project

With HTTP polling, every sensor would need to be queried at fixed intervals whether or not anything changed — which creates unnecessary network and server load once many sensors are involved. MQTT works on a publish/subscribe basis: sensors send values as they occur, and the backend only subscribes to the relevant data streams. That's more bandwidth-efficient and holds up better against the short connection drops that can occur on building networks.

Building sensors often come from different manufacturers and report data in different formats and at different intervals. A platform has to map that variety onto a single, consistent interface before the data can be processed further — that's one of the core jobs of the sensor connectivity layer.

Python has a wide ecosystem of libraries for handling time-series data and adapts relatively quickly to new sensor types or data formats. For a backend that continuously prepares heterogeneous sensor data, that adaptability is a practical advantage.

Display devices in a building typically operate without continuous on-site supervision. If a device briefly drops offline or loses its connection, it needs to update its content on its own once it reconnects rather than showing outdated material. A central management system handles that control and keeps an overview of every display's status.

NDVDL supports Smartenic with IoT, networking and digital signage: connecting the sensors, transmitting readings in real time over MQTT, processing them in the Python backend, the network foundation behind it and the central management of the displays. The cooperation is ongoing.

Because every device, sensor and display needs a working connection — and because IoT devices are a risk of their own when they sit unsegmented next to workstations and servers. Planning, segmentation and coverage of the network therefore decide whether the sensor data arrives reliably and whether the devices endanger the rest of the operation.

Question not covered here?

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Services this project demonstrates

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