Smart Automation System for Office Environment

A smart automation system for office environment is being designed in this system. Various controlling systems based on lighting, ventilating, luminance are discussed respectively. Various sensors are used to extract the real time information i.e. temperature, light intensity, humidity, smoke, motion sensor are used. This data is send to ARM 11 Controller. It is then send to PC where data is saved. Through Network switch this data is send to other PC’s. The data collected is stored as database and can be accessed anytime. The data is send to the android or any internet enabled device. This system also provides need based emergency services like Ambulance call, fire alarm. Biometric fingerprint is used for security purpose. Manual mode and automatic mode are two alternative modes designed to promote the usability of smart office system. Control of electric lighting fixtures of different office spaces is done

An adaptive IoT architecture using combination of concept-drift and dynamic software product line engineering

Internet of things (IoT) architecture needs to adapt autonomously to the environment and operational to maintain their supreme services. One common problem in the IoT architecture is to manage the reliability of data services, such as sensors’ data, that only sending data to the collector via gateway. If there is a disruption of services, then it is not easy to manage the system reliability. To this, an adaptive environment which is based on software reconfiguration creates a great challenge to provide better services. In this work, the software product line engineering (SPLE) reconfigures the edge devices via rules and software architecture. To identify disruption of data services which can be detected based on anomaly and truncated data. Our work makes use of concept drift to provide a recommendation to the system manager. This is important to avoid misconfiguration in the system We demonstrate our method using an open-source internet of things portal system that integrated to a cluster of sensors which is attached to specific gateway before the data are collected into a cloud storage for further processes. In identifying drifting data, the adaptive sliding window (ADWIN) method outperforms the Page-Hinkley (PH) with more selective identification and sensitive reading

A Resource-based Rule Engine for energy savings recommendations in Educational Buildings

Raising awareness among young people on the relevance of behaviour change for achieving energy savings is widely considered as a key approach towards long-term and cost-effective energy efficiency policies. The GAIA Project aims to deliver a comprehensive solution for both increasing awareness on energy efficiency and achieving energy savings in school buildings. In this framework, we present a novel rule engine that, leveraging a resource-based graph model encoding relevant application domain knowledge, accesses IoT data for producing energy savings recommendations. The engine supports configurability, extensibility and ease-of-use requirements, to be easily applied and customized to different buildings. The paper introduces the main design and implementation details and presents a set of preliminary performance results

A novel Rule-based Semantic Architecture for IoT Building Automation Systems

The ever growing number of smart devices connected to the Internet of Things is giving users the chance to sense data from surrounding environment and act upon it. However, interpreting raw data coming from heterogeneous sensors and applying control algorithms to actuators is not a simple task for the common end-user who wants to create applications for smart environments. For these reasons, this work deals with the definition of a novel rule-based semantic architecture for the implementation of building automation applications in an IoT context. Sensor data are abstracted at a high semantic level related to the properties they are associated to and interactions with actuators are driven by high-level desired actions. Applications have the form of an Event- Condition-Action (ECA) rule and the layered architecture separates high-level semantic reasoning aspects from low-level execution details. The proposed architecture is also compared with main state-of-the-art solutions and some suitable technologies for its implementation are suggested