Eternal connections between all things relentlessly trace the atavistic patterns of the synaptic framework of our minds.

Industrial IOT

The digitization process, the robust development of new languages and software libraries and, above all, the emergence of important cloud platforms have led modern industry to make the most of these innovation factors to dramatically increase production efficiency. Today, thanks to the Industrial Internet of Things, every single department, every single machine and every element of the production system is interconnected.

The key element that definitively connects the manufacturing world to the digital world is the edge, a bridge between heaven and hell.


La Proposta di Valore di Sinaptica 4.0



Riduzione dei costi

Riduzione del TimeToMarket

Minore complessità gestionale

Riduzione dei rischi di Failure


Servizi proposti


Sviluppo software

Data Analisys



Valore aggiunto

Maggiore efficienza

Controllo dei processi

Maggiore qualità del prodotto

Supporto alle decisioni


We install and program EDGE devices, such as the Siemens IOT2040, which are able to collect any type of data from production lines managed by PLC and send it to databases in the cloud or on the company intranet. EDGE devices are the connection bridge between the production environment and the data collection center.

Industrial machines, now endowed with senses, see, hear and touch everything that’s part of its natural habitat.

The IIoT has created a new type of data which affects each level of the manufacturing ecosystem. Machines, software, devices, sensors, users, locations and even dynamic elements, such as processes and events, real or anticipated, connect, consume and produce a never before seen amount of new data. Small and medium-sized manufacturers can connect their entire business, regardless of protocols, processes, age or equipment location.

Advantages in the installation of IIoT systems.

Real-time remote control of production processes

Storage and analysis of data from production processes

Implementation of artificial intelligence algorithms for predictive analysis of maintenance phases

Decision-making processes based on a comprehensive view of all company mechanisms

Increased production efficiency due to more focused choices

Decreased employee presence required within the company

Improvement of plant automation processes

Greater ability to plan workflow

Optimization of warehouse stock