Best Dash Cam With Gps Tracking
Raul Herrera
The following servers as a guide to highlight the structure of my newer Dash application. The ideas presented in this guide come from my own experience working as in intern in a large React project and common attributes found in open source repositories across the web.
The .env file is where you should house any passwords or keys. This is a common practice as we do not want to directly hardcode keys into your application where a malicious actor could see them. Some common values found in .env files are DATABASE_URI or API_KEY. Later on in this guide, we will see how the data is loaded.
The README.md file should specify how to install and run your application. This includes, but is not limited to, installing packages, mentioning which environemnt variables need to be set, and running the application.
The components directory should contain common components used throughout the application. The simplest example are that of the navigation bar, navbar.py, and footer element, footer.py. All-in-one components should also be stored here. Defining each of these components in their own file is good practice. Additionally, I import each component into the __init__.py file. This allows for easier imports like the following:
Large structured applications rely on the new Dash Pages feature, currently only available via Dash Labs. This guide will be updated once Dash Pages is included in an official Dash release. For more information, see the community post at -dash-pages-a-dash-2-x-feature-preview/57775.
The pages directory houses the individual pages of your application. I split the pages into 2 categories, static and complex pages. The static pages are ones that do not have any, or minimal callbacks, such as your home, privacy policy, about, 404 not found, or contact page. The complex pages are ones that contain more complex layouts and callbacks.
The api.py file reads in our environment variables to get the API_KEY. The sample API called does not require a key; however, I deemed it important to include anyways. This file also defines a function that formats the inputs to call the API. To call the API, we just need to import and call the get_number_fact(int) method.
The images.py file focuses on anything to do with images shown in our application. Some of the main functionality includes reading in local images and converting them to encoded strings so they show up properly. Addtionally, if you are displaying images hosted on some Content Distribution Network (CDN), you might also define a method for formatting the url here.
As it stands, Dash requires the app object for defining long_callbacks. Since this is the only place in the codebase that can access the app object, without ciruclar imports, this file should house any long_callbacks.
Hi @raptorbrad I was wondering if you have a recommendation for how to integrate testing into this structure? From reading the docs for dash.testing it seems to assume having test files at the same level as app.py. So how can we integrate this with pages, and how can we use the usual tests folder?
I started working on some unit testing around when Dash 2.6 released; however, I ran into some import errors. I believe these have since been fixed, so its just a matter of time before someone (myself included) opens a pull request into this repo to address them.
adding to the great information Kishan posted I believe, while it is a basic requirement, it depends on the team what they want to see and which kind of representation of the data is the best for them.
Some time ago there was a blog post published by Atlassian which in my opinion gives a lot of inspiration. If you want to read and compare if this is useful for the metrics your team wants to see you can have a look here:
How did you go defining what you need and researching the marketplace? @Daniel Ebers thanks for the link to the post on how to build a killer dashboard. I hadn't seen it; really cool and totally on point.
It powers up more team insights by connecting your Jira, Bitbucket, Confluence and Chat (Slack or mattermost presently). In this way we map how your agile delivery team designs, builds, reviews and engages for your sprint or kanban intervals.
Hi Mayuresh, have you explored the out of the box gadgets available in JIRA already ? eg: - Created vs Resolved Chart, Issue Statistics, Issues in progress, Pie Chart, Sprint Burndown Gadget. You can use them as well to track number of issues, their status, sprint burndown chart to track remaining work etc. Or are you looking for third party plugins ?
Hello! I'm interested in building a small JIRA dashboard to display metrics around user story estimate efficiency. This is not an effort to grade developers or "burn" people for poor estimates, more just to see how good we are at estimating and whether we get better over time.
Unfortunately, JIRA does not have a dashboard gadget that sums the values of specific fields, like time spent or original estimate upon a release. It would be necessary to display the sum of those values to display the three reports you are looking for.
Any of the apps above provide you with some Gadgets that you can create upon a JQL filter configured to return your release. Those gadgets can display the sum of the issues, Original estimate and Time Spent, or even the same details for each issue or user in your release.
I am building processes for my new employer and I am struggling to build an efficient Time-tracking system for projects (Boards) and tasks (Items)
We have several projects managed on separate boards, with several stages (groups) and multiple tasks (items) on which multiple members of the staff work on and report. We want to track time spent on individual task and on individual projects by members of staff by week/month.
I have added a time tracking column on each item and created a dashboard where I want to monitor progress through the following views:
Hi all, have been using Monday for time tracking for some time now but am wanting to extract more useful data in reports.
Am I correct in thinking that the only option for adding any kind of time tracking based reporting in a dashboard is to add the time tracking widget, which can only show total time tracked for certain people/dates/groups?
Fleet managers should take advantage of a new breed of dash cams designed for them as intelligent information sources. From high-quality video to driver behavior data collection, truck dash cams go far beyond the simple consumer units sold in Big Box stores.
The right dashboard camera will also work in tandem with your truck tracking system to allow monitoring and management of your drivers and fleet. Professional grade truck dash cams should include these key features:
Depending on your application, the top truck dash cams on your list may be the ones that survive a tough work environment or take extra measures to ensure data integrity. Some units still rely on vehicle power and restart when power is lost, but others now provide a backup battery to ensure that data is recorded even if power is lost during an accident.
Perhaps the most essential feature for dashcams used in commercial trucking, upon which legal cases might rest and operations depend, is their durability, with rugged construction and even IP68 waterproof and dustproof cases.
Commercial-grade truck dash cam units go the extra mile to ensure that the video they capture is high-quality whether you're driving on a bright, sunny day or in the dark of night. Many of the best units use sophisticated video processing electronics to keep the picture sharp even in low light, while others add LED-based lighting of the road ahead for excellent night recording.
As dash cam units available to the consumer at Big Box stores and Amazon become ever more sophisticated, fleet managers may wonder: why not just use the same technology used by commuters and in family cars?
The answer is simple: top truck dash cam manufacturers know what the industry needs. With so many features available in truck dash cam equipment, it's likely that you will have to decide whether to purchase one that has the most desirable features, the best features for your truck or fleet's activities, or perhaps the one with the most potential for the future.
They help identify speed limit signs, road hazards, distracted driving, illegal U-turns, rolling stops and the truck's position relative to other vehicles and highway lane markers. Just as jet pilots receive altitude and other safety reminders, the Advanced Driver Assistance System (ADAS) features help avoid the need to record and resolve an en-route incident.
Concrete video evidence can save hundreds of thousands in insurance settlements in the case of an accident. Bottom-line benefits from daily use include safer driving, more efficient routing, decreased risk of general moving violations and improved training opportunities.
The NSTSCE found that when combined with driver coaching, dash cams can reduce safety-related events as much as 52%. Beyond improving driver safety, dash cams are a great way to lower costs and save money. Here are five main benefits of dash cams with GPS tracking:
Decrease insurance-related costs: When it comes to insurance premiums, safety is a big factor. Because dash cams are proven to improve safety and mitigate risk, your insurance company may offer a premium discount, credit, or subsidy for installing dash cams and sharing safe driving data for each of your fleet vehicles.
Reduce vehicle wear and tear: Harsh braking wears out brake pads and causes unnecessary stress on vehicles. Dash cams can play in-cab alerts when safety-related events are detected, helping to discourage harsh driving and reduce physical damage and maintenance costs.
Retain more drivers and reduce labor costs: It may seem surprising, but dash cams can reduce labor costs in a few different ways. Your back-office team can build an effective fleet safety program and coach drivers more efficiently with digital driver safety scorecards and video-based coaching tools. Plus, data and footage from dash cams can help create a robust safety rewards program, which is proven to increase engagement and retention, leading to lower turnover and hiring costs.
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