We have built a platform for people to Create, Store & Manage geo-location data to answer their day-to-day questions. In other words, we provide GPS based advanced location tracking services, with offerings in this space for individuals, organizations and businesses looking for end-to-end solution & support.
We offer GPS | GSM | GPRS Trackers with SaaS (Software as a Service) Platform accompanied by an integrated cloud-telephony infrastructure for 3rd person perspective usage.
During our extensive 3 years long research in GPS domain at TrackNerd GPS, we found that although GPS technology has been there for quite some time and its requirement in personal space has existed since it has only been put to use for navigation or other 1st Person perspective usage. With TrackNerd GPS we are trying to cater to a 3rd person perspective usage like parents that are looking to track whereabouts of their child, especially kindergarten-to-6 class; not with an intent of policing but for peace of mind and security. So we looked at this scenario and tried to find a solution with the intent of making least changes in their current routine. So we came up with TrackNerd Shadow; half the size of a mobile phone, for your kid and tracking services for you in the cloud.
TrackNerd pursues R&D in Telematics, M2M Communication, Machine Learning and IOT domain.
Telematics: TrackNerd GPS devices, relies on GSM to communicate with the server and comes
pre-installed with a service SIM card.
There are 2 kinds of communication happening between the hardware device and server in the cloud:
Machine Learning: There are two key sets of algorithms that differentiate us from our competitors and allow us to offer a RELIABLE tracking solution to our end users.
M2M Communication: To address the reliability issues of current personal GPS tracker solutions available in the market, TrackNerd GPS completely changed the way end user services were delivered. In spite of relying on hardware device for end-user services, we fused it with cloud server by implementing M2M communication between the two and offered services through the server. To do so, we not only had to create an innovative GSM-Internet mashup infrastructure but also develop Machine Learning algorithms for geo-location data interpretation on run time and device behaviour control modules that are briefly explained above.
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