Developing a Campus Wide Building Information System Based on Open Standards

Buda, Andrea; Kinnunen, Tuomas; Dave, Bhargav; Främling, Kary

doi:10.24928/jc3-2017/0338

Cited by 2 publications

(3 citation statements)

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“…(ii) We compare several IoT architectures based on different characteristics as well as formulate the functional and non-functional requirements of our proposed architecture. (iii) The capabilities of IoTEF are assessed by applying them to the smart buildings use case of the ongoing Otaniemi3D project at Aalto University campus in Otaniemi [8,9].…”

Section: The Contributions Of This Paper Are Threefold: (I)mentioning

confidence: 99%

“…To evaluate the capabilities of our proposed architecture, we consider a smart buildings use case of the ongoing Otaniemi3D project. The proof-of-concept for Otaniemi3D has earlier been developed by the Aalto University researchers [8,9], where Otaniemi is the name of university campus and 3D represents the dimensions in which IoT data are presented. Smart buildings are generally equipped with a Building Management System (BMS) that incorporates smart interconnected technologies to perform intelligent and responsive operations, such as fault detection, make automatic adjustments, alert management staff, and monitor performance.…”

Section: Case Study: Smart Buildingsmentioning

confidence: 99%

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IoTEF: A Federated Edge-Cloud Architecture for Fault-Tolerant IoT Applications

et al. 2020

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The evolution of Internet of Things (IoT) technology has led to an increased emphasis on edge computing for Cyber-Physical Systems (CPS), in which applications rely on processing data closer to the data sources, and sharing the results across heterogeneous clusters. This has simplified the data exchanges between IoT/CPS systems, the cloud, and the edge for managing low latency, minimal bandwidth, and fault-tolerant applications. Nonetheless, many of these applications administer data collection on the edge and offer data analytic and storage

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Section: The Contributions Of This Paper Are Threefold: (I)mentioning

confidence: 99%

Section: Case Study: Smart Buildingsmentioning

confidence: 99%

IoTEF: A Federated Edge-Cloud Architecture for Fault-Tolerant IoT Applications

et al. 2020

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“…For proof-of-concept, a smart campus, in the subcategory of smart city, is selected as an IoT environment, in which sensors are available in public areas. This smart campus is called Otaniemi3D [4], which provides information about energy consumption, occupancy, and user comfort by integrating Building Information Models (BIMs) and IoT devices through open standards called Open Messaging Interface (O-MI) and Open Data Format (O-DF). O-MI provides a communication framework between products and distributed information systems which consume and publish information on a real-time basis.…”

Section: Introductionmentioning

confidence: 99%

MeDI: Measurement-based Device Identification Framework for Internet of Things

Yousefnezhad

Madhikermi

Främling

2018

2018 IEEE 16th International Conference on Industrial Informatics (INDIN)

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IoT systems may provide information from different sensors that may reveal potentially confidential data, such as a person's presence or not. The primary question to address is how we can identify the sensors and other devices in a reliable way before receiving data from them and using or sharing it. In other words, we need to verify the identity of sensors and devices. A malicious device could claim that it is the legitimate sensor and trigger security problems. For instance, it might send false data about the environment, harmfully affecting the outputs and behavior of the system. For this purpose, using only primary identity values such as IP address, MAC address, and even the public-key cryptography key pair is not enough since IPs can be dynamic, MACs can be spoofed, and cryptography key pairs can be stolen. Therefore, the server requires supplementary security considerations such as contextual features to verify the device identity. This paper presents a measurement-based method to detect and alert false data reports during the reception process by means of sensor behavior. As a proof of concept, we develop a classification-based methodology for device identification, which can be implemented in a real IoT scenario.

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Developing a Campus Wide Building Information System Based on Open Standards

Cited by 2 publications

References 0 publications

IoTEF: A Federated Edge-Cloud Architecture for Fault-Tolerant IoT Applications

IoTEF: A Federated Edge-Cloud Architecture for Fault-Tolerant IoT Applications

MeDI: Measurement-based Device Identification Framework for Internet of Things

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