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Applications of Machine Learning – Fire Detection
Published in Rashmi Priyadarshini, R M Mehra, Amit Sehgal, Prabhu Jyot Singh, Artificial Intelligence, 2023
R. M. Mehra, Rashmi Priyadarshini
The detectors of a central alarm system are all connected to a central controller and relay their signals to it immediately. When the controller receives alarm input from the detecting sensors, it activates warning devices such as horns, strobe lights, and speakers to alert the inhabitants. Central alarm and evacuation systems are becoming increasingly connected and intelligent. Mass notification systems now include a paging component that transmits live audio instructions across the site in the case of an emergency. Most mass notification systems now include a wide range of emergency messages, including severe weather warnings, security alerts, and amber alerts, among others. One of the most advanced features of mass notification systems is the ability to send SMS, text, email, popup, app message, and push notifications to specified recipients, enabling for fast and effective awareness. Because of the IoT and other current technology, progress is conceivable. It can also be used in emergency situations. Sensor and detector data, as well as other monitoring data, may be used with algorithms and analytics to aid in the development of better emergency or evacuation plans. To improve evacuation preparations, analytics may examine a variety of factors, including the number of people in the building, building maps, the location of the fire, and the rate at which the fire spreads, as well as the fire’s direction. Analytics-based evacuations plans can assist minimize crowding by guiding individuals from various parts of the building to the most effective evacuation path.
A Review on IoT Architectures, Protocols, Security, and Applications
Published in Anand Sharma, Sunil Kumar Jangir, Manish Kumar, Dilip Kumar Choubey, Tarun Shrivastava, S. Balamurugan, Industrial Internet of Things, 2022
Dilip Kumar Choubey, Vaibhav Shukla, Vaibhav Soni, Jitendra Kumar, Dharmendra Kumar Dheer
The work deals (Dawson-Haggerty et al., 2010) with a RESTful architecture that allows devices and other producers of physical information to directly publish their data. (Kovatsch et al., 2010) proposed a REST/HTTP framework for Home Automation. (Mayer et al., 2010) proposed a toolkit/framework which permits the user to decide if there is data traffic to be exchanged over an IoT network. There is a need for new standard protocols that are based on standard Web technologies but that consider the limitations of constrained devices. Recently, Internet Engineering Task Force (IETF) Constrained RESTful environments (CoRE) Working Group has proposed a REST-based web transfer protocol called Constrained Application CoAP (Shelby et al., 2013), a standard over UDP that specifically addresses the prerequisites of the constrained nodes carrying sensors and actuators in many deployments. These nodes/smart objects usually run specialized operating systems such as (Dunkels et al., 2004). For the realization of RESTful environments, CoAP focuses on a binary HTTP-inspired open protocol, providing features such as resources discovery and subscription for a resource (resulting in push notifications). MQTT by IBM is a lightweight messaging protocol based on a unified publish/subscribe approach. It is designed for constrained devices and low bandwidth, high latency, or reliable networks requirements. In a similar fashion, MQTT-S is a cut-down version of the MQTT protocol, which is geared toward lossy radio protocols work in (Yasser, 2014) deals with various aspects of security challenges in context with cloud computing, issues mentioned in the document also require consideration and further investigation need to be articulated in context with IoT environment.
Smart Cities and Urbanization: The Urge of Machine Learning and IoT
Published in Amit Kumar Tyagi, Niladhuri Sreenath, Handbook of Research of Internet of Things and Cyber-Physical Systems, 2022
In traditional environment, the data is not processed at the same place where it is generated. processing and analysis of data is a timing consuming process because involves transferring of data from storage centers to processing centers. So, traditional environment is not suitable for IoT generated data as it requires quick analysis and processing. Cloud computing has become ubiquitous due to its provisioning of multiple environments as services for various kinds of software applications. It has the capability of storing and processing high volumes of data. The huge volume of data, and need for large processing would increase cloud server CPU usage. Cloud computing in general classified as below: Infrastructure as a Service (IaaS): The organizations buys all the equipment including computers, servers, networks, and hardware need to run the appliance.Platform as a Service (PaaS): Assists the developers in developing and deploying applications and services on the internet. PaaS services can be access by developers and user in a web browser.Software as a Service (SaaS): The providers deliver software based on common set of code and data. SaaS is a leased software maintained by its providers based on usage metrics.Backend-as-a-Service (BaaS): It is a cloud service model where all the back-end aspects of a web or mobile application are provided. The developers code and maintain only front end. BaaS is pre-written software for all the server-side functionality, like user authenticity, data managing, and push notifications, cloud storage and hosting.
Privacy risk in contact tracing systems
Published in Behaviour & Information Technology, 2023
Bluetooth is widely used in contact tracing apps for ‘proximity tracing’ in which the proximity of app users is measured when they are near each other for a certain amount of time as defined by health experts. In proximity contact tracing, users install an app that is assigned a unique ID. With their device’s Bluetooth feature turned on, app users broadcast a unique Bluetooth ID to nearby devices with the same app. When two devices are in proximity of each other (e.g. 2 m) for a certain time threshold (e.g. 15 min), the two devices exchange and store each other’s unique ID. The history of app user IDs a person has encountered is either stored on the phone or uploaded to a central computer server in the possession of public health agents. The purpose of a central server is threefold: (1) to retrieve and broadcast the IDs of infected individuals; (2) to send push notifications to app users in case of a match; and (3) to map the network of an infected person’s contacts. When an app user is diagnosed positive with the disease, a confirmation is sent to that user’s smartphone either upon the user’s consent or automatically by a health agent. Next, all app users whose IDs were stored as proximity contacts are identified as possible receivers of the virus and will be notified either via the app, SMS (text) or a phone call. Contact tracing apps using this approach include TraceTogether (Singapore) (Bay et al. 2020) and Covidsafe (Australia) (Australian Government Department of Health 2020).
“Free Food on Campus!”: A Novel Use of Instructional Technology to Reduce University Food Waste and Feed Hungry Students
Published in Journal of Hunger & Environmental Nutrition, 2021
Laura B. Frank, Emily M. Finkbinder, Virginia S. Powell
An important aspect of FFOC that distinguishes it from other campus food rescue operations is its ease of setup and use, and the absence of cost to implement and maintain the service. Modern colleges and universities already possess and utilize electronic learning management systems to present online components of their courses to students. With this framework in place, setting up the enrollment and announcement mechanism is simple. Also, both students and faculty know how to use the system without further training. In contrast to the FFOC use of the existing system, some other programs have required the development of an app by a team of technical personnel and the involvement of multiple campus entities. For example, the implementation of “Titan Bites” at California State University, Fullerton was described as follows: Developed by Auxiliary Services Corp.’s Campus Dining Services, Student Life and Leadership, Associated Students Inc. (ASI) and the Division of Information Technology, the app is part of the University’s ongoing efforts to address food and housing insecurity on campus … Students interested in signing up for Titan Bites should log in to their campus portal, click on the “Settings” icon in the top right corner and scroll to the “Student Account Settings” section. By clicking the “Edit” button next to the “Join Titan Bites Free Food Program on Campus” setting, they can designate whether they would like to receive push notifications via email or SMS notification … Four campus organizations — OC Choice Catering, ASI, Student Life and Leadership, and the Gastronome — currently have approval to push real-time notifications through Titan Bites.26
The digital ‘connected’ earth: open technology for providing location-based services on degraded communication environments
Published in International Journal of Digital Earth, 2018
Ramón Piedrafita, Rubén Béjar, Rubén Blasco, Alvaro Marco, F. Javier Zarazaga-Soria
Therefore, it was decided to use the GCM service to send Push notifications (Bell, Bleau, and Davey 2011) to Android nodes. This service allows sending and receiving messages between the server and the nodes without knowing the IP addresses of the nodes, which may change over the time. The Push Notifications service associates with each node a unique identification ID, in such a way that the server sends messages to the GCM service with the node ID.