什么是MileIQ？ (What Is MileIQ?)

MileIQ is a mileage tracking app that automatically tracks drives for classification as business vs. personal. For users, it eliminates the time to track drives with a written log, produces the required documentation for tax purposes, and can save them money by maximizing their tax deduction and/or company mileage reimbursement. For companies, it can also save them money by ensuring the proper amount is reimbursed, and/or provides the required tax documentation for vehicles they may deduct.

MileIQ是一个里程跟踪应用程序，可以自动跟踪驱动器，以将其分类为企业还是个人。 对于用户而言，它省去了用书面日志跟踪驱动器的时间，为税务目的提供了所需的文档，并可以通过最大程度地减少税款和/或公司里程补偿来节省资金。 对于公司而言，它还可以通过确保退还适当的金额来为他们省钱，和/或为他们可能扣除的车辆提供所需的税务文件。

The mission of the app is to capture drives accurately without any human intervention. MileIQ uses the last known endpoint for one trip as the start point for the next trip. MileIQ needs at least a half-mile (0.8 km) difference in reported location to recognize a new trip. Depending on where the last known location data came from (cell tower, WiFi Hotspot, etc.) and where the next data point comes from, there can be up to a mile (1.6 km) variance for MileIQ to know that a new trip has started. Drives under a mile (1.6 km) may occasionally be disregarded due to this variance. And once a drive has been detected, MileIQ takes roughly 15 minutes to determine whether the user has reached a settled state. It is only at this point, MileIQ will download the drive card and displays it in the app.

该应用程序的任务是准确捕获驱动器，而无需任何人工干预。 MileIQ使用一次旅行的最新已知终点作为下一次旅行的起点。 MileIQ需要在报告的位置至少相差半英里(0.8公里)才能识别新行程。 根据最后一个已知位置数据的来源(蜂窝塔，WiFi热点等)以及下一个数据点的来源，MileIQ最多可以了解英里(1.6公里)的变化，以了解新行程开始。 由于这种差异，有时可能会忽略一英里(1.6公里)以下的行驶。 一旦检测到驱动器，MileIQ大约需要15分钟来确定用户是否已达到稳定状态。 仅在这一点上，MileIQ将下载驱动器卡并将其显示在应用程序中。

通用驱动器质量反馈 (Common drive quality feedback)

Any app that uses background location has to balance battery life and location accuracy. For MileIQ, this trade-off can result in some customer complaints about drive quality.

使用后台位置的任何应用都必须平衡电池寿命和位置准确性。 对于MileIQ，这种折衷可能导致一些客户抱怨驱动器质量。

1. Missed drives :

   缺少的驱动器：

As the name suggests the app would have failed to track some drives. Though we allow customers to add the missed drives manually via the dashboard, it again acts as an overhead to the customer.

顾名思义，该应用程序将无法跟踪某些驱动器。 尽管我们允许客户通过仪表板手动添加丢失的驱动器，但这再次成为客户的开销。

Example: Let’s say a user has taken a drive from 10.00 am to 10.10 am covering 2 miles. Since the distance is very small, the app did not receive high precision locations signals to distinguish the mode of transportation. Hence the drive has not been recorded and resulted as a Missed drive. Now the user is forced to add the drive manually either through the app or web dashboard.

示例：假设某个用户从上午10.00到上午10.10行驶了2英里。 由于距离非常小，因此该应用程序未收到用于区分运输方式的高精度位置信号。 因此，尚未记录该驱动器，并导致该驱动器丢失。 现在，用户被迫通过应用程序或Web仪表板手动添加驱动器。

2. Delayed departure :

2.延迟出发：

Sometimes, the MileIQ app would have not woken up after a geofence exit during the start of the drive for various reasons like low battery, the app got killed by the OS, etc. During these times, the app would have missed the actual start time of the drive, and instead, it will take the next timestamp where the app gets woken up as its starting time.

有时，由于各种原因(例如电池电量低，应用程序被操作系统杀死等)，在驱动器启动过程中退出地理围栏后，MileIQ应用程序可能不会醒来。在这段时间内，该应用程序会错过实际的启动时间驱动器，而是将应用程序唤醒的下一个时间戳记作为其开始时间。

Example: Let's say the user started to drive 20 miles away and turned on the app at 12:57 pm before arriving and reached the destination at 1:05 pm. The processed drive, in this case, would tell the user that he has covered 20 miles in 8 minutes, instead of actual duration which might be 40 min.

示例：假设用户开始开车20英里远，并在下午12:57开启应用程序，然后在下午1:05到达目的地。 在这种情况下，经过处理的驱动器将告诉用户他在8分钟内已经行驶了20英里，而不是实际持续时间(可能是40分钟)。

蓝牙如何帮助解决问题？ (How Bluetooth helped to solve the problem?)

Our team has worked on overcoming the missed drives and delayed departure scenario, by improving our drive detection logic with the help of the user’s Bluetooth information.

我们的团队通过在用户的蓝牙信息的帮助下改善了我们的驾驶检测逻辑，致力于克服错过的驾驶和延迟出发的情况。

MileIQ used a combination of location and motion events to determine the start of the drive. But we have seen cases where these events are not 100% accurate resulting in missed drives/delayed departure drives.

MileIQ使用位置和运动事件的组合来确定驱动器的启动。 但是，我们已经看到了这些事件并非100％准确的情况，导致驱动器丢失/出发驱动器延迟。

However Bluetooth connection events are more reliable than the location and motion events. And moreover, we do not need only the location event to determine the start of the drive. Consistent Bluetooth events strongly indicate the user’s presence in the vehicle.

但是，蓝牙连接事件比位置和运动事件更可靠。 而且，我们不需要位置事件即可确定驱动器的启动。 一致的蓝牙事件强烈表明用户在车辆中。

We will see an example to understand how Bluetooth events create an impact on a drive.

我们将看到一个示例，以了解蓝牙事件如何对驱动器产生影响。

Drive without Bluetooth packet:

没有蓝牙数据包的驱动器：

Let’s consider a user is planning to take a ride from point A to point B. He starts his ride at 10.00 am and reaches the destination at 10.30 am. The drive will get processed and will show that the user has taken a drive from 10.10 am to 10.35 am. The delay in the start time is because the app takes some time to confirm that the user has really started to move.

让我们考虑一个用户计划从A点到B点乘车的情况。他从上午10.00开始乘车，然后在上午10.30到达目的地。 该驱动器将得到处理，并显示用户已从上午10.10到上午10.35进行了驱动器。 启动时间的延迟是因为该应用需要花费一些时间来确认用户确实已经开始移动。

Drive with Bluetooth packet:

带蓝牙数据包驱动：

Let’s consider another user planning to take a ride from point A to point B. She starts her ride at 10.00 am and as soon as she gets into her car, her phone gets auto-connected to her Bluetooth vehicle. She reaches the destination at 10.30 am. The drive packet which has information about the location and her Bluetooth connection/disconnection information will get processed and will show her that the drive has started from 10.00 am. The delay in the start time is getting fixed automatically.

让我们考虑另一个计划从A点骑行到B点骑行的用户。她从上午10点开始骑行，一旦上车，她的手机就会自动连接到蓝牙车辆。 她于上午10.30到达目的地。 具有有关位置信息和其蓝牙连接/断开连接信息的驱动器数据包将得到处理，并向她显示驱动器已从上午10.00开始启动。 开始时间的延迟将自动固定。

Another good example of using Bluetooth information is when she is stuck in traffic. At present, when she is still for more than 10 to 15 minutes, the app tries to complete the drive and the further journey is considered as another fresh drive. But with Bluetooth information, we can be sure of these kinds of incidents. If she has an active connection, it means that she has not moved away from the vehicle probably stuck in traffic.

使用蓝牙信息的另一个很好的例子是当她遇到交通阻塞时。 目前，当她静止10到15分钟以上时，该应用会尝试完成该驱动器，而进一步的行程则被视为另一个新驱动器。 但是有了蓝牙信息，我们就可以确定发生此类事件。 如果她的连接处于活动状态，则表示她没有离开可能阻塞交通的车辆。

我应该如何将蓝牙用于MileIQ (How should I leverage Bluetooth for MileIQ)

The only prerequisite to make use of this feature is that the user has to add their Bluetooth vehicle to the MileIQ app.

要使用此功能，唯一的先决条件是用户必须将其蓝牙工具添加到MileIQ应用中。

With your device already paired to your vehicle:

设备已与车辆配对时：

1. Go to Vehicles in MileIQ by navigating to Menu > Account Settings > Personalization > Vehicles, and then tap on Add Vehicle.

   通过导航至菜单>帐户设置>个性化>车辆 ，进入MileIQ中的车辆 ，然后点击添加车辆 。

2. In the next screen, tap Add via Bluetooth to scan for your vehicle.

   在下一个屏幕中，点击“ 通过蓝牙添加”以扫描车辆。

3. Select your vehicle (or vehicle’s Bluetooth designation, i.e. ‘Handsfreelink’ in the example below) from the list.

3.从列表中选择您的车辆(或车辆的蓝牙名称，即以下示例中的“ Handsfreelink” )。

4. On this screen, set your vehicle options, and tap on More Details to enter vehicle details such as make/model/odometer reading.

4.在此屏幕上，设置您的车辆选项，然后点击更多详细信息以输入车辆详细信息，例如品牌/型号/里程表读数。

5. When finished, tap on Save to add the vehicle into MileIQ.

5.完成后，点击保存将车辆添加到MileIQ。

The Bluetooth tracking algorithm is designed in a flexible way, such that it works as expected even when the mobile phone starts to support multiple Bluetooth connections at a single instance in the future.

蓝牙跟踪算法的设计方式非常灵活，即使将来移动电话开始在单个实例中支持多个蓝牙连接时，它也可以按预期工作。

影响力 (Impact)

After releasing the feature to production, customer satisfaction with the drive quality saw measurable improvement.

在将该功能投入生产后，客户对驱动器质量的满意度得到了可观的提高。

学分 (Credits)

1. Thanks to ravi krishnan, Sachin Srivastava , manish kataria, Amit Singh, and Sarang Deshpande for brainstorming and constant guidance throughout the project.

   多亏了ravi krishnan ， 萨钦塔瓦 ， 马尼什卡塔利亚 ， 阿米特·辛格 和 萨朗德什潘德 在整个项目中进行头脑风暴和不断指导。

2. Thanks to Cesar Valiente, Max Wheeler, Neal Bernstein, Jasbir Khalsa, Akshath Shetty, and Sumita Jaiprakash for the amazing feedback in the article.

   感谢Cesar Valiente ， Max Wheeler，Neal Bernstein，Jasbir Khalsa， Akshath Shetty 和 Sumita Jaiprakash的出色反馈。