Grenoble Institute of Technology

About: Grenoble Institute of Technology is a education organization based out in Grenoble, France. It is known for research contribution in the topics: Hyperspectral imaging & Geology. The organization has 3427 authors who have published 5345 publications receiving 137158 citations. The organization is also known as: Grenoble INP.

Design and Development of an IoT Based Smart Irrigation and Fertilization System for Chilli Farming

Abstract: India is an agricultural country and 70% of the people directly or indirectly depends on agriculture for their living. Nowadays, water scarcity is one of the main challenges faced by the farmers. Another major challenge faced by Indian agriculture sector is the increase in rate of farmers suicide because of debt. So, effective measures have to be devised in order to reduce the cost of farming and increase the yield from agriculture. This research work proposes the design of a generic IoT framework for improving agriculture yield by effectively scheduling irrigation and fertilization based on the crops current requirements, environmental conditions and weather forecasts. This work proposes the design of an affordable irrigation and fertilization system. The proposed fertilization system spreads fertilizers to the root directly. This reduces the amount of fertilizers required and thus reduces the cost and improves the soil health. A user friendly mobile application has been designed to deliver this information to the farmers in their regional language. The generic framework has been validated using a case study for chilli farming.

Feasibility of BCI Control in a Realistic Smart Home Environment.

Abstract: Smart homes have been an active area of research, however despite considerable investment, they are not yet a reality for end-users. Moreover, there are still accessibility challenges for the elderly or the disabled, two of the main potential targets for home automation. In this exploratory study we design a control mechanism for smart homes based on Brain Computer Interfaces (BCI) and apply it in the “Domus” smart home platform in order to evaluate the potential interest of users about BCIs at home. We enable users to control lighting, a TV set, a coffee machine and the shutters of the smart home. We evaluate the performance (accuracy, interaction time), usability and feasibility (USE questionnaire) on 12 healthy subjects and 2 disabled subjects. We find that healthy subjects achieve 77% task accuracy. However, disabled subjects achieved a better accuracy (81% compared to 77%).

Orientation Maps Derived from TEM Diffraction Patterns Collected with an External CCD Camera

Abstract: An automatic crystallographic orientation indexing procedure is developed for transmission electron microscopes. The numerical identification is performed by mapping the spot diffraction patterns with pre-calculated templates. The diffraction patterns are acquired thanks to an external CCD camera that points to the fluorescent screen through the TEM window. Orientation maps with spatial resolution better than 10 nm were obtained with this low cost equipment.