Smart City

Smart City

Model of a smart city with electrical components (IOT) accompanied by a mobile application (Android)

Internet of Things

  • 2 Collaborators



Model of a smart city with electrical components (IOT) accompanied by a mobile application (Android): The invention concerns a miniature prototype simulating a smart city comprising IoT components (Intel Edison card, temperature / sound / gas sensors,...) with a mobile application inter-communicating to provide functionalities to the citizens of the smart city:

  • Remote parking.
  • Public Wifi Park with electrical outlets in order to charge phones or computers.
  • Intelligent store for automatic delivery of products.
  • Noise pollution detection.
  • Detection of gas.

and other functionalities for the management of the city:

  • Economic management of the electricity of the lightpoles (by detection of the passing objects).
  • Temporal organization of road traffic lights.
  • Automatic irrigation of green areas.

The user can therefore use the application to benefit from the provided services, and be notified in case of danger in order to improve the standard and quality of life, comfort and safety.



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Rima M. updated status

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Rima Modak

I am currently working to develop a prototype of an device based on IoT. This device will be used to detect any kind of material. It will be used to detect both living and non-living things, and after detecting, it will display varies other things related to the detected object according to the tags provided by the user/customer.

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Aravindhan N. created project Automatic attendance management system using face detection

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Automatic attendance management system using face detection

Automatic attendance management system will replace the manual method, which takes a lot of time and is difficult to maintain.There are many bio metric processes ,in that face recognition is the best method. In our campus staff attendance is taken with the help of Gesture recognition /attendance sheet .We can take this to next level by implementing Artificial Intelligence based Face Recognition using Convolution Neural Network(CNN). We have to train our neural net using COCO (large Image dataset designed for object detection) and Staff Dataset (Several images of individual staffs). Since we don't have the photos of the staffs,we have trained our neural net using our own photos.Our Neural net consists of 20 neurons in the hidden layer which help us to diagnose the pixels of the image and compares the result with the trained dataset .By using our advanced system the staffs can use their own mobile/laptop [camera] for registering their presence in their own place which is possible only if they are connected to our college Network (WiFi).

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Cory Potter

Empowering everyone to grow a more sustainable future by harnessing the power of technology and nature.

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Roberto Diaz Morales

I am currently the leader of the Data Science research line at Treelogic where I take part in many European H2020 research projects. My research interest include large scale Machine Learning, Parallelization and Deep Learning techniques. I obtained my PhD and Master Degree from the University Carlos III in Madrid where I worked under the supervision of Ángel Navia Vázquez. My Ph.D. research consisted in the parallelization of kernel methods, a family of of Machine Learning algorithms like Support Vector Machines (SVMs) or Gaussian Processes (GPs). My hobbies include taking part in Machine Learning competitions, such as those organized by Kaggle where I have received prizes in many competitions and I have reached the top 100 of the world ranking of data scientist.

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