Realisasi Sistem Switch Lampu Penerangan Ruangan Otomatis Untuk Meningkatkan Efisiensi Energi Listrik

Penghematan energi listrik sangat bergantung pada perilaku dan kesadaran manusia. Sekitar 80% keberhasilan kegiatan konservasi energi ditentukan oleh faktor manusia, sedangkan 20% lagi bergantung teknologi dan peralatan. Salah satu solusi alternatif dalam permasalahan ini adalah menerapkan sistem otomasi sehingga secara otomatis menghidupkan dan mematikan lampu ruangan dengan mendeteksi keberadaan manusia di dalam ruangan. Dalam penulisan ini melakukan realisasi rancangan  agar dapat dimanfaatkan oleh masyarakat sebagai fitting ekstensi otomatis dalam upaya penghematan daya listrik. Penelitian ini juga membandingkan disipasi daya yang timbul saat lampu tidak menyala dengan lampu sensor gerak yang ada di pasaran.  Realisasi rancangan terdiri dari dua sistem yaitu, menggunakan sensor PIR terintegrasi pewaktu NE555 dan sensor PIR terintegrasi mikrokontroler Atmega 8 SMD. Hasil yang dicapai adalah, disipasi daya lampu sensor gerak  type LED di pasaran adalah 6,2 Watt, lampu penerangan ruangan otomatis terintegrasi pewaktu IC555 lebih efisien 79,26% dibandingkan lampu sensor gerak di pasaran, lampu penerangan ruangan otomatis terintegrasi mikrokontroler atmega 8 lebih efisien 60,39% dibandingkan lampu sensor gerak di pasaran. Kata Kunci: Efisiensi, Lampu Otomatis, Light Fitting, Mikrokontroler, Sensor gerak, Time

IoT*(Ambisense): Smart environment monitoring using LoRa

In this work, IoT* (AmbiSense), we present our developed IoT system as a solution for Building and Energy Management using visualization tools to identify heuristics and create automatic savings. Our developed prototypes communicate using LoRa, one of the latest IoT technologies, and are composed of a set of battery-operated sensors tied to a System on Chip. These sensors acquire environmental data such as temperature, humidity, luminosity, air quality, and also motion. For small to medium-size buildings where system management is possible, a multiplatform dashboard provides visualization templates with real-time data, allowing to identify patterns and extract heuristics that lead to savings using a set of pre-defined actions or manual intervention. LoBEMS (LoRa Building and Energy Management System), was validated in a kindergarten school during a three-year period. As an outcome, the evaluation of the proposed platform resulted in a 20% energy saving and a major improvement of the environment quality and comfort inside the school. For larger buildings where system management is not possible, we created a 3D visualization tool, that presents the system collected data and warnings in an interactive model of the building. This scenario was validated at ISCTE-IUL University Campus, where it was necessary to introduce the community interaction to achieve savings. As a requested application case, our system was also validated at the University Data Center, where the system templates were used to detect anomalies and suggest changes. Our flexible system approach can easily be deployed to any building facility without requiring large investments or complex system deployments.Nesta dissertação de mestrado, IoT * (AmbiSense), é apresentado um sistema IoT desenvolvido como uma solução para Gestão de Edifícios e Energia recorrendo a ferramentas de visualização para identificar heurísticas e criar poupanças automáticas. Os protótipos desenvolvidos comunicam utilizando LoRa, e são compostos por um conjunto de sensores ligados a um microcontrolador alimentado por bateria. Os sensores adquirem dados como temperatura, humidade, luminosidade, qualidade do ar e movimento. Para edifícios de pequena e média dimensão onde a gestão do sistema é possível, um dashboard fornece templates de visualização com dados em tempo real, permitindo extrair heurísticas, que introduzem poupanças através de um conjunto de ações predefinidas ou intervenção manual. O sistema LoBEMS (LoRa Building and Energy Management System), foi validado numa escola local durante um período de três anos. A avaliação do sistema resultou numa poupança de energia de 20% e uma melhoria significativa da qualidade do ambiente e conforto no interior da escola. Para edifícios de maior dimensão onde a gestão do sistema não é possível, criámos uma ferramenta de visualização 3D, que apresenta os dados e alertas do sistema, num modelo interativo do edifício. Este cenário foi validado no campus do ISCTE-IUL, onde foi necessária a interação da Comunidade para obter poupanças. Foi nos também solicitada uma validação do sistema no centro de dados da Universidade, onde os templates do sistema foram utilizados para detetar anomalias e sugerir alterações. A flexibilidade do sistema permite a sua implementação em qualquer edifício, sem exigir um grande investimento ou implementações complexas

Security scheme for wireless sensor network

A Wireless Sensor Network (WSN) could be a network created of tiny autonomous sensors (nodes). Its purpose is to watch environmental variable like temperature, pressure, humidity, motion, brightness, etc. These nodes use a radiofrequency system to deliver the knowledge gathered by the sensors to a central process unit (CPU) or base station. The communication between a node and therefore the base station may happen either directly or step by step through completely different nodes among the network. Some WSN can even be controlled from the base station. Each device node typically consists of the subsequent main components: a microcontroller, completely different sensors, a radio transceiver and electric battery or another supply of power. The scheme relies on LOCK scheme and staff ID-based secure cluster key management. The scheme has many blessings over the prevailing LOCK theme. This scheme improves the wireless device network system security. It minimizes the amount of key storage demand and therefore the number of the communication messages for rekeying. Additionally, one distinctive advantage is that it doesn't have an effect on the other nodes once evicting compromised node or moving the node from one location to a different. The goal of this thesis is to style and build a WSN node and to program its microcontroller thus it covers a basic practicality, implement the science security and to send the collected knowledge to different network nodes

Advanced Occupancy Measurement Using Sensor Fusion

With roughly about half of the energy used in buildings attributed to Heating, Ventilation, and Air conditioning (HVAC) systems, there is clearly great potential for energy saving through improved building operations. Accurate knowledge of localised and real-time occupancy numbers can have compelling control applications for HVAC systems. However, existing technologies applied for building occupancy measurements are limited, such that a precise and reliable occupant count is difficult to obtain. For example, passive infrared (PIR) sensors commonly used for occupancy sensing in lighting control applications cannot differentiate between occupants grouped together, video sensing is often limited by privacy concerns, atmospheric gas sensors (such as CO2 sensors) may be affected by the presence of electromagnetic (EMI) interference, and may not show clear links between occupancy and sensor values. Past studies have indicated the need for a heterogeneous multi-sensory fusion approach for occupancy detection to address the short-comings of existing occupancy detection systems. The aim of this research is to develop an advanced instrumentation strategy to monitor occupancy levels in non-domestic buildings, whilst facilitating the lowering of energy use and also maintaining an acceptable indoor climate. Accordingly, a novel multi-sensor based approach for occupancy detection in open-plan office spaces is proposed. The approach combined information from various low-cost and non-intrusive indoor environmental sensors, with the aim to merge advantages of various sensors, whilst minimising their weaknesses. The proposed approach offered the potential for explicit information indicating occupancy levels to be captured. The proposed occupancy monitoring strategy has two main components; hardware system implementation and data processing. The hardware system implementation included a custom made sound sensor and refinement of CO2 sensors for EMI mitigation. Two test beds were designed and implemented for supporting the research studies, including proof-of-concept, and experimental studies. Data processing was carried out in several stages with the ultimate goal being to detect occupancy levels. Firstly, interested features were extracted from all sensory data collected, and then a symmetrical uncertainty analysis was applied to determine the predictive strength of individual sensor features. Thirdly, a candidate features subset was determined using a genetic based search. Finally, a back-propagation neural network model was adopted to fuse candidate multi-sensory features for estimation of occupancy levels. Several test cases were implemented to demonstrate and evaluate the effectiveness and feasibility of the proposed occupancy detection approach. Results have shown the potential of the proposed heterogeneous multi-sensor fusion based approach as an advanced strategy for the development of reliable occupancy detection systems in open-plan office buildings, which can be capable of facilitating improved control of building services. In summary, the proposed approach has the potential to: (1) Detect occupancy levels with an accuracy reaching 84.59% during occupied instances (2) capable of maintaining average occupancy detection accuracy of 61.01%, in the event of sensor failure or drop-off (such as CO2 sensors drop-off), (3) capable of utilising just sound and motion sensors for occupancy levels monitoring in a naturally ventilated space, (4) capable of facilitating potential daily energy savings reaching 53%, if implemented for occupancy-driven ventilation control

A robust system for counting people using an infrared sensor and a camera

In this paper, a multi-modal solution to the people counting problem in a given area is described. The multi-modal system consists of a differential pyro-electric infrared (PIR) sensor and a camera. Faces in the surveillance area are detected by the camera with the aim of counting people using cascaded AdaBoost classifiers. Due to the imprecise results produced by the camera-only system, an additional differential PIR sensor is integrated to the camera. Two types of human motion: (i) entry to and exit from the surveillance area and (ii) ordinary activities in that area are distinguished by the PIR sensor using a Markovian decision algorithm. The wavelet transform of the continuous-time real-valued signal received from the PIR sensor circuit is used for feature extraction from the sensor signal. Wavelet parameters are then fed to a set of Markov models representing the two motion classes. The affiliation of a test signal is decided as the class of the model yielding higher probability. People counting results produced by the camera are then corrected by utilizing the additional information obtained from the PIR sensor signal analysis. With the proof of concept built, it is shown that the multi-modal system can reduce false alarms of the camera-only system and determines the number of people watching a TV set in a more robust manner. © 2015 Elsevier B.V. All rights reserved

Innovative low power multiradio sensing and control device for non-intrusive occupancy monitoring

New tools and methodologies to reduce the gap between predicted and actual energy performances at the level of buildings and blocks of buildings are in continuous development in academic and industry organizations. The development of Wireless Sensor Networking (WSN) technology plays a core role in this field since their development enables the monitoring and control of application within the building environment. In this paper the development of a low power consumption multiradio and multisensing system to monitor building conditions and enable the interaction of occupants with devices through embedded actuators is described. The device (named NOD) incorporates a 32-bit ARM-Cortex microcontroller, a variety of sensors to monitor the ambient conditions – luminance, temperature, humidity, air quality - and multiple radio interfaces - WiFi/Bluetooth LE/868MHz. The NOD is intended to be used as a desktop device with a dedicated user interface. A description of the system and its features and functionalities is provided