Construction Information Technology Programming

The aim of the course for students is to apply and deepen previously got programming knowledge (object-oriented Python programming) in Building Management Systems field. Students get familiar in application of IT methods in BMS field based on simplified models of widely used solutions, services of buildings. Resource-effective and secure applications are implemented while perfection is got in terminology, typical and specific tasks, standards of BMS. Potential projects: 1. Geoinformatics, Image Processing: the base is a spatial point cloud of a building (or building part), students need to use programming tools to clean the point cloud, identify simple, typical building objects, derive dimensions. 2. Energetics: based on a software of hardware (IoT) environment of a building, students create energy management system. The goal is a building model consist of scalable environmental impacts (temperature, illumination), energy loss of the building/walls, and the heating system (traditional combined with the one using renewable energy). Students need to harmonize these systems, create appropriate control management, and prove its working by reports/queries. 3. Intelligent building: the model described above is to be extended by the elements of an intelligent house, i.e., sensors, safety, and comfort services (e.g., wind sensor, actuators for shading screens, cameras and window/door sensors and actuators, controlling lighting and entertainment systems. Student will obtain creative services in this context/environment. 4. Building safety/security: Security and safety solutions (security sensors, fire detectors to minimize damage and improve safety level). 5. Facility management: students are modelling the aging of the building, the deterministic and stochastic events, are estimating operating costs, scheduling maintenance actions (considering Industry 4.0 concepts). 6. IoT-based Building Management: IoT tools monitoring the building and its environment are to be used for the above-mentioned tasks, solutions. From the acquired data the accuracy level of estimates can be improved to save the quality of the building, its safety level, considering comfort and effective operation. Students learn the basics and strengths of Big Data analysis and Deep Learning. Projects are supported by hardware and software modelling elements, practically a building simulation environment is prepared. Students must create software solutions in above fields using sensors and activators of the model building starting from prepared application structures.

Module with associated contact hours

Mandatory literature:; 1. Krishnan Saravanan (Author, Editor), Golden Julie (Editor), Harold Robinson (Editor): Handbook of Research on Implementation and Deployment of IoT Projects in Smart Cities (Advances in Civil and Industrial Engineering) 1st Edition, 2019, ISBN 978-1522591993; 2. Digital source for used libraries (listed during the course);  ; Recommended literature:; 3. Adriana X Sanchez, Keith Hampson, Geoffrey London: Integrating Information in Built Environments, 2018, ISBN 9781138706323; 4. Peter Wentworth, Jeffrey Elkner, Allen B. Downey, Chris Meyers: How to think like a Computer Scientist, 2012.

Python programming

Requirements: General rules   The final grade results from • preparation of the project task in cooperative form (specification, coding, documentation, acceptance by lecturers)  • presenting the project at the end of the semester   Evaluation system   Project task: 70% Project presentation: 30% Sum 100%   Requirements and validity of signature The requirement of the signature is successfully preparing and presenting project task. Grading system   Excellent P > = 92 Good 91 > P >= 84 Satisfactory 84 > P >= 76 Pass 76 > P >= 68 Fail 68 > P   The project task preparation gives 70 points, the oral and documented presentation gives 30 points. Additional possibilities: Based on electronic notes published for the subject.

Programming (BMEVIHIA061 or BMEEODH001)