Passerelle, an IoT Smart System

Passerelle, an IoT Smart System

Passerelle is a Smart System applicable by enterprises in the domains of energy, mobility, telecom and environment.

What are the advantages of the Internet of Things ?

Appliances primed for the Internet of Things are equipped with intelligent sensors and measurement points. Such appliances have existed for a long time. The measurements they perform are collected and sent to an administrator electronically and securely. They also support the communication that passes between the measurement point and a central system such as a control room.

The Internet of Things in the home environment, isn’t that all about fridges refilling themselves and window shutters communicating with your central heating? Well, perhaps it is. But what’s more important for you as entrepreneur, have you ever wondered :

what could this renowned IoT mean for your business ?


Smart Systems implicate automated adjustments and decisions

Measurements bring only knowledge after interpretation of the measured sensor data.
A Smart System could for instance supervise (smart monitoring), perform additional analysis of the data, or send out alerts. Enterprises can adjust their processes and automate decisions based on this stream of information.

An enterprise Smart System can function on different levels:

  • Collect data about the usage and performance of a system in order to design a new, more efficient version of that system.
  • Collect, process and present data to help an operator or user in taking correct decisions.
    For example : a smart traffic system can detect traffic jams and offer alternative routes to drivers.
  • Use collected data to perform automated actions without human intervention.
    For example : a system could send out alerts when air pollution thresholds are crossed.

On a larger scale we can combine the data streams of varying type of sensors to a smart infrastructure, aimed at improving processes that are results from the interactions between different child processes.
A typical example here is a Smart Grid which adjusts energy production to local consumption.

The components of a Smart Infrastructure

  • Data
    Everything start with data … lots of data. A huge amount of data forms the epicenter of each smart infrastructure. The system must be able to process data from different sources and in varying formats.
  • Analysis
    By applying the right mathematical models on correct, selective samples of that data, or by meticulously combining data, the system can transform separate, meaningless facts to valuable information. That information can then form the basis for reliable decision making.
  • Decision Making
    The system contains a rules engine for manual, semi-automated, or fully automated decision making.
  • Feedback
    A smart infrastructure must be able to collect input from a variety of systems simultaneously and use that data for continuous optimization. This cycle of data feedback is fundamental in allowing adjustable decision making.

Smart Systems and Passerelle

Passerelle is a Smart System which is already being applied by enterprises in the domains of energy, mobility, telecom and environment.
In telecom enterprises, for instance, it is being used for remote monitoring and maintenance of thousands of appliances in user premises. It allows suppliers to deliver a much improved and efficient customer service.

The following steps are needed to solve problems in such an environment in an efficient way:

  • Fast diagnosis to identify the cause of telecom problems
  • Proper determination of actions that could correct the problem
  • Selection and implementation of the correct repair actions

The First Time Right principle, which implies speed as well as correctness, is essential in this process. But without proper tooling, the repair process becomes extremely error prone and expensive. A technician who is sent to a client’s premises without supporting software can never have all the required expertise. The experience of colleagues, whom are not readily available, may be required. This could cause considerable delays in the repair process. Problems that only occur sporadically are even harder to diagnose without proper tooling. By the time the technician arrives at the premises to make measurements of the telecom equipment, sporadic problems may already have disappeared, only to reemerge when he has left.

In such contexts, Passerelle is an indispensable support tool for field engineers. It collects remote data in the complex telecom infrastructure and provides further analysis and diagnosis. In some circumstances, Passerelle can go even further by applying repairs on the equipment automatically. The advantages of this tooling are clear: improved efficiency, faster solutions, lower costs, and an augmented ‘First Time Right’.

The advantages of Passerelle as a smart system

  • Employees can collect relevant information (sensor data) remotely.
  • People with widely differing skills can collaborate closely within an integrated system.
  • Specialist knowledge is centralized and is accessible in a uniform manner.
  • Flows for analysis and diagnosis provide guidance in interactive troubleshooting.
  • Problem solving can become fully automated.
  • Historical repair knowledge allows detection of maintenance needs and can lead to maintenance automation.

Predictive Maintenance

Prevention is better than cure. A smart infrastructure should not suffer component failure or unforeseen downtime.
In this area, Passerelle offers additional value: through continuous monitoring of critical parameters, problems can be detected at an early stage. Through intelligent analysis of historical data and events, Passerelle can send out warnings when maintenance or interaction are called for. Subsequently, Passerelle can perform semi-automated or fully automated repair actions. On the basis of these actions, further intervention needs can be adjusted.

So Predictive Maintenance involves the possibility to predict the occurrence of ‘desirable events’. With continuous monitoring and analysis of events, combined with predictive models, proper corrections can be applied to attain the desired effect.

2017-06-19T14:23:27+00:00 June 1st, 2017|Blog, In the picture|
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Automation of Knowledge Intensive Business Decisions
Knowledge Management
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Dirk Jacobs
Erwin De Ley