Transforming The Future Of Logistics With Geocoding
We live in a world where extensive data is available in a click. With real-time traffic updates and location services, one would assume that the logistics industry would consume this to increase their efficiency. Sadly, that is not the case. Logistics has primarily been just a ‘pick, pack and ship’ process. In order to retain customers, most companies weave together a “temporary” solution by hiring more workforce instead of adopting technology. This is a failing formula that increases the cost to business without being sustainable on a longer term. Logistics and its colossal challenges Shipping a parcel from one location to another is quite straightforward. The complexity of delivering any product increases with the number of drop locations. As the volume increases, the system is beyond the scope of humans to comprehend. Number of locations to visit Number of ways to visit all locations 1 1 3 6 5 120 9 Grains of sand in 1 kg of sand 21 Atoms in 1 grain of sand 22 Also, grains of sand on Earth, including deserts. 24 Stars in the known Universe Considering real-world uncertainties and various business constraints, timely decision making to deliver shipments efficiently is a vexing issue. In the year 2016, according to Google, there were 100 million online shoppers in India amounting to a market that is worth Rs 2 lakh crores this year. In spite of the massive potential, companies remain deep-seated in the primitive state of logistics that is sluggish to technology adoption. Logistics plays a significant loop back to enhance consumer brand experience, hence compelling E-com companies to invest in efficient and consistent delivery process. Last-mile delivery alone amounts to 35% of the total delivery cost. Inefficiency in  delivery process directly impacts productivity, revenues and customer experience of the companies. Some of the complex logistics challenges that exist are – Limited visibility of on-field fleet and workforce Lack of real-time coordination Locating exact delivery drop off points Manual dependencies in parcel sorting & route allocation While packing and routing are essential optimization problems in logistics, often the primary challenge is to identify the exact delivery locations attached to shipments. In countries such as India, where the address system is ‘descriptive’ rather than ‘formatted’, geocoding can get very difficult. Further, addresses that have ambiguous landmarks can  complicate the matter. Geocoding – Turning addresses into coordinates We at Locus.sh have built advanced geocoding solutions that combine machine learning, natural language processing and rule-based improvements to gather complete address information. Our solutions capture not only the diversity in address formats but also the diversity in language and the scripts in which addresses are provided. Geocoding is the process of converting a human written address to global coordinates (latitude & longitude pairs) which are unambiguously understandable by machines. In case of Google geocoder, its autocorrecting feature is remarkable because of its ability to suggest you “correct” localities as you type. However, this feature becomes inept as the details get more granular because the addresses are already provided by the end users and the inability to fix the errors by prompting possible alternatives. Most geocoding APIs are inefficient without the option of “suggestions” partially because of the missing “context”. Locus geocoding API help find the most accurate coordinates for the address under consideration, precise to door number, lane and locality. A significant reason for the success of Locus geocoder is the access to a high volume of address data that our clients share with us along with the delivery information associated with those addresses. As the size of data increases so does our geocoding accuracy leading to more profitable and optimized delivery routes. Our excellence in geocoding and routing has allowed us to introduce a range of solutions our customers that incorporates real-world fuzziness such as unpredictable networks, dirty location points and various business constraints (Like SLA). Locus’ technology platform offers end to end logistics solutions such as – Auto-sortation – Intelligent parcel sorting system leveraging our geocoding expertise, allowing warehouses to sort incoming orders into their optimal delivery routes Route optimization – Right deliveries to the right resources at the right time using our proprietary routing engine 3D Packing engine – Intuitive loading plan for multidimensional cargo into containers which ensure vehicle optimisation Business intelligence for strategy planning – Unified dashboard for tracking the performance of delivery agents and providing location-based performance What sets us apart is our intelligent routing engine which, purely based on client feedback, is the only optimization engine to work at scale in India. Locus’ robust technology platform works seamlessly on-ground that incorporates real-time factors and 100s of exceptional scenarios such as real-time traffic, volume, fuzzy data. We have a unique system which serves multiple verticals, right from new age on-demand, to traditional FMCG movement. Indian logistics arena – Exigent need to adopt technology With increased awareness among digital consumers, the focal point for businesses has shifted towards consumers, factoring in 3 key areas – Experience, Delight & Retention.
We live in a world where extensive data is available in a click. With real-time traffic updates and location services, one would assume that the logistics industry would consume this to increase their efficiency. Sadly, that is not the case. Logistics has primarily been just a ‘pick, pack and ship’ process. In order to retain […]
We live in a world where extensive data is available in a click. With real-time traffic updates and location services, one would assume that the logistics
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["business intelligence", "Go", "API", "machine learning", "AI", "ML", "Git", "RAG", "ViT", "R"]
["AI", "machine learning", "ML", "RAG", "R", "Go", "Git", "API", "ViT", "business intelligence"]
Shantanu S. Bhattacharyya did his Ph.D. from Carnegie Mellon University (Pittsburgh, USA) in the field of molecular and structural biology. He then moved to The Scripps Research Institute (TSRI) for his post-doctoral work where he developed and used computational prediction tools for vaccine design against HIV. Shantanu holds a B.Sc. degree from University of Delhi where he was awarded the National Science Fellowship (KVPY) for four years (end of Masters degree) 
Shantanu is currently leading the geocoding project at Locus. He uses a combination of natural language processing (NLP), machine learning algorithms like recurrent neural networks (RNN) and different statistical methods to interpret human written addresses and convert them to computer understandable co-ordinates. For countries like India, where addresses are error prone and descriptive instead of formatted, geocoding is a primary hurdle in automation of decision making in logistics.
He also uses the location data to provide intelligence on rider reliability, changing business demand etc for various clients.