Sensoring Networks

  Sensity Porto Networks

Sensity Porto For Future Places 2020. I was invited to go and talk and exhibit Sensity in Portugal  

Sensing Porto senses the environment to make live visualization and sonification of the city of Porto. Made using custom made sensors to measure, light, noise, sound, humidity, and temperature....this data is turned into a real time visualization of the space which was exhibited. The sensors where laid out across the city to take a snapshot of one day in the life of the city.

This is a five year old company, with a staff of 35 employees and world leader in the development, production and installation of sensing systems based on optical fibre Bragg gratings.
What does this mean exactly? It means that we are actually exporting Portuguese “grey matter” in some glass-like strings with software applications, and that two doctorates in optical physics - Francisco Araújo and Luis Ferreira – left the giants Siemens and Airbus struck with astonishment.
But the CEO of Fiber sensing, the spin-off company from INESC Porto (Institute for Systems and Computer Engineering of Porto), can explain it better.
"Airbus wanted to measure the level of strain in the fuel tanks of their commercial airplanes. Nowadays, apart from Fiber sensing, any supplier requires two sensors to measure strain: a strain and a temperature sensor. Fiber sensing has developed, invented and patented a strain sensor that is capable of self-compensating itself temperature wise. It’s something that doesn’t exist anywhere else in the world. When we presented this to Airbus, they were stunned and couldn’t believe what they were seeing ", Sergio Acetonic states.
But today, Fiber sensing "millionaire contract" gets the signature of Siemens Power Generation, in Orlando, United States. "We have a multilingual contract with Siemens for vibration monitoring in high power generators for nuclear power plants.

Sensor Networks

This project involved the development of a network architecture that allows a variety of sensor technologies to be mounted on a mobile robotic system independent of the hardware configuration of the system's control computer. The architecture provides ease of expansion and modification to a sensor network with little modification required to the network interface software running on the control computer. A network of conventional mid-long range sensors has been constructed to implement and test the network architecture.
Johnny's role...
Johnny designed the network architecture and hardware behind the sensor network. He developed the firmware to control both infrared position sensitive detectors and ultrasonic transducers as well as the firmware for providing a managed network access controller to allow network communications. He has written the C# based libraries that allow future users to rapidly develop applications to configure and receive data from a sensor network.
     Sensor nodes can be imagined as small computers, extremely basic in terms of their interfaces and their components. They usually consist of a processing unit with limited computational power and limited memory, sensors or MEMS (including specific conditioning circuitry), a communication device (usually radio transceivers or alternatively optical), and a power source usually in the form of a battery. Other possible inclusions are energy harvesting modules, secondary ASICs, and possibly secondary communication devices.
    The base stations are one or more components of the WSN with much more computational, energy and communication resources. They act as a gateway between sensor nodes and the end user as they typically forward data from the WSN on to a server. Other special components in routing based networks are routers, designed to compute, calculate and distribute the routing tables. 
   Johnny constructed a prototype sensor network that was mounted to a mobile robotic security guard platform and developed a user interface, built on top of the C# libraries, to display data received from the sensor network.

Calling all cars: cell phone networks and the future of traffic 

 In this in-depth look at the Mobile Millennium project, Arstechnica examines the technology behind a distributed automotive sensor network.

We'll look at how the system is designed to protect user privacy, examine how data from thousands of mobile phones and hundreds of static sensors are combined to measure traffic flow, and look at how this technology will impact the future of driving.

Designing and running these sensor networks is no trivial task. Data is flooding in from many different sources in many different places, and useful data has to be separated from noise. Algorithms and models are needed to fuse the incoming data into a comprehensible whole, and protecting individual privacy is also a major challenge. Yet the potential gains are huge, so there is an unceasing demand for more and better data.
 

In this article, Arts goes behind the scenes at Mobile Millennium to examine the technology behind a distributed sensor network. We'll look at how the system is designed to protect user privacy, examine how data from thousands of mobile phones and hundreds of static sensors are combined to measure traffic flow, and look at how this technology will impact the future of driving

Aggregate Sensor Networks

  

Aggregate can be easily used to monitor multiple  sensors and operate complex control logic. Let's say you operate a huge organic greenhouse. Your greenhouse always has to be in a certain temperature and humidity percentage. These variables keep changing at various times of the day, and as equipment and workers enter and leave the warehouse.

Your sensor grid, deployed throughout the warehouse, could connect to Aggregate server and constantly relay sensor data. When a certain threshold is crossed (i.e, humidity too low) an alert could be raised, and corrective action will automatically occur - water atomizers would kick in, adding humidity.

You could generate reports to easily see how much power and water your greenhouse consumes, and use the data to plan the space layout more efficiently and minimize any waste of resources

A wireless sensor network (WSN)

 consists of spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. and to cooperatively pass their data through the network to a main location. The more modern networks are bi-directional, also enabling control of sensor activity. The development of wireless sensor networks was motivated by military applications such as battlefield surveillance; today such networks are used in many industrial and consumer applications, such as industrial process monitoring and control, machine health monitoring, and so on.

The WSN is built of "nodes" – from a few to several hundreds or even thousands, where each node is connected to one (or sometimes several) sensors. Each such sensor network node has typically several parts: a radio transceiver with an internal antenna or connection to an external antenna, a micro controller, an electronic circuit for interfacing with the sensors and an energy source, usually a battery or an embedded form of energy harvesting. A sensor node might vary in size from that of a shoebox down to the size of a grain of dust, although functioning "motes" of genuine microscopic dimensions have yet to be created. The cost of sensor nodes is similarly variable, ranging from a few to hundreds of dollars, depending on the complexity of the individual sensor nodes. Size and cost constraints on sensor nodes result in corresponding constraints on resources such as energy, memory, computational speed and communications bandwidth. The topology of the WSNs can vary from a simple star network to an advanced much-hop wireless mesh network.