Group Task 5: Secondary Research

Group Task 5: Secondary Research

Interesting articles:

An IoT Based Air Pollution Monitoring System for Smart Cities
https://www.researchgate.net/publication/334092485_An_IoT_Based_Air_Pollution_Monitoring_System_for_Smart_Cities

Air quality all around the world, and in cities especially, is decreasing and air pollution is cited responsible for millions of deaths per year worldwide, according to WHO. According to the article, the solution to this problem is smart cities and IoT air quality control devices that are, e.g. based on Raspberry Pi 3 Model B with sensors, a cloud data storage platform and an API/dashboard. With these sensors we can track qualities like temperature, humidity, carbon monoxide, smoke, gases and concentration of hazardous particular matter. The article is based around an Android app while the data is stored privately on ThingSpeak and is requested through the API through HTTP requests. The data stream is sensors (analog to digital converter depending on sensory output) -> Raspberry Pi -> ThingSpeak -> JSON format -> application.

Efficient IoT-based sensor BIG Data collection–processing and analysis in smart buildings
https://www-sciencedirect-com.ezproxy.turkuamk.fi/science/article/pii/S0167739X17314127

In this paper the authors try to collect, transmit and analyse the enormous amounts of data produced by IoT devices, transmitted through the internet and to the cloud environment. They propose efficient smart building network architecture, and they use an operating system called Contiki and emulator Cooja to simulate their proposed network design in real time. The authors also explore other related works, such as "An indoor location-aware system for an IoT-based smart museum" -article, in which the authors designed and validated an indoor location-aware architecture which is able to enhance the user experience in a museum. The system relies on wearable device that combines image recognition and localization capabilities. This system interacts with the cloud with the aim to store multimedia contents that is produced by the user and to share environment-generated events on user’s social network.

IoT-based Occupancy Monitoring Techniques for Energy-Efficient Smart Buildings
https://www.researchgate.net/publication/280157569_IoT-based_Occupancy_Monitoring_Techniques_for_Energy-Efficient_Smart_Buildings

Development of Internet of Things (IoT) devices such as smartphones, sensors, cameras, and RFIDs, has made collection of data from these devices for tracking and localization purposes possible. Data collection is done via WiFi (WiFi-based), use of cameras (camera-based) or sensor-based. WiFi-based data collection involves installation of packet analyzers which captures incoming packets. These packets are further captured using tcpdump and forwarded to servers for MAC address and RSSI value collection. Camera-based collection makes use of cameras to detect motion. With the aid of motion, occupancy in a building can be collected. Human face, head, upper body, are for example, used by the algorithm to make counting. Sensor-based make collection of data using microcontroller with WiFi support, such as Arduino. With Arduino, different kinds of variables can be inputted for calculation / counting. Data collected from these IoT devices are from various type of occupancy sensors which are generally places within buildings. Occupancy can be further divided into detection, counting, tracking and behavior recognition. Occupancy detection gives data about the space and if empty. This is generally done in meeting places or cafeterias. Occupancy counting gives data about the number of people in a place at a given time. It can count total number of people in the whole building or sectors of the building. Occupancy tracking provides data from people by counting, locating and tracking them. Occupancy behavior analyzes people behavior in a space by using data from occupancy detection.

Interesting products/services/applications/concepts:

Envira IoT – Structural health monitoring of buildings
https://enviraiot.com/structural-health-monitoring-of-buildings/

Using sensors to monitor the structural health of buildings, technologies include REST, MQTT, 3G, LTE, LORA. Data is transferred to a platform where it can be graphically displayed and downloaded for further analysis. It allows for real time monitoring of structures and buildings, extensive logging enables studies of trends in the behaviour of fissures.

Urban.io
https://www.psitechnologies.com/product-lines/smart-buildings-iot-urban-io/

Urban.io provides a range of low cost, industrial grade IoT devices that provide real time data from building systems. For example, using IoT sensors to detect a failure in cool rooms and freezers.  Adding sensors that provide real time data of such rooms to alert if the temperature rises too high. This leads to reduced costs, since the spaces don’t have to be inspected manually multiple times a day.

FSG Smart Buildings
https://www.fsgsmartbuildings.com/services/iot

Using multiple IoT sensors to monitor and control buildings. For example, automatic temperature control etc. They work with multiple sensors like temperature, humidity, co2, activity detection and vibration to name a few. They have a platform named Chariot that is a cloud-based management plane for the IoT sensors and provides real time monitoring.